no code implementations • IWSLT (ACL) 2022 • Bao Guo, Mengge Liu, Wen Zhang, Hexuan Chen, Chang Mu, Xiang Li, Jianwei Cui, Bin Wang, Yuhang Guo
Our system is built based on the Transformer model with novel techniques borrowed from our recent research work.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
1 code implementation • COLING 2022 • Zhongjian Miao, Xiang Li, Liyan Kang, Wen Zhang, Chulun Zhou, Yidong Chen, Bin Wang, Min Zhang, Jinsong Su
Most existing methods on robust neural machine translation (NMT) construct adversarial examples by injecting noise into authentic examples and indiscriminately exploit two types of examples.
no code implementations • NAACL (AutoSimTrans) 2022 • Mengge Liu, Xiang Li, Bao Chen, Yanzhi Tian, Tianwei Lan, Silin Li, Yuhang Guo, Jian Luan, Bin Wang
This system paper describes the BIT-Xiaomi simultaneous translation system for Autosimtrans 2022 simultaneous translation challenge.
1 code implementation • ACL 2022 • Bin Liang, Chenwei Lou, Xiang Li, Min Yang, Lin Gui, Yulan He, Wenjie Pei, Ruifeng Xu
Then, the descriptions of the objects are served as a bridge to determine the importance of the association between the objects of image modality and the contextual words of text modality, so as to build a cross-modal graph for each multi-modal instance.
no code implementations • ECCV 2020 • Chi Xu, Yasushi Makihara, Xiang Li, Yasushi Yagi, Jianfeng Lu
Specifically, a phase estimation network is introduced for the input single image, and the gait cycle reconstruction network exploits the estimated phase to mitigate the dependence of an encoded feature on the phase of that single image.
no code implementations • CCL 2021 • Xiang Li, Chengwei Liu, Xiaoxu Zhu
“反问是现代汉语中一种常用的修辞手法, 根据是否含有反问标记可分为显式反问句与隐式反问句。其中隐式反问句表达的情感更为丰富, 表现形式也十分复杂, 对隐式反问句的识别更具挑战性。本文首先扩充了汉语反问句语料库, 语料库规模达到10000余句, 接着针对隐式反问句的特点, 提出了一种融合情感分析的隐式反问句识别模型。模型考虑了句子的语义信息, 上下文信息, 并借助情感分析任务辅助识别隐式反问句。实验结果表明, 本文提出的模型在隐式反问句识别任务上取得了良好的性能。”
1 code implementation • ACL 2022 • Bin Liang, Qinglin Zhu, Xiang Li, Min Yang, Lin Gui, Yulan He, Ruifeng Xu
In this paper, we propose a joint contrastive learning (JointCL) framework, which consists of stance contrastive learning and target-aware prototypical graph contrastive learning.
no code implementations • 18 May 2024 • Tianxin Zhou, Xiang Li, Haibing Lu
Hence, the problem of locating the most critical or vulnerable transmission lines for a Power Grid Cascading Failure (PGCF) has drawn much attention from the research society.
no code implementations • 18 May 2024 • Wuzhou Li, Jiawei Zhou, Xiang Li, Yi Cao, Guang Jin, Xuemin Zhang
In this paper, we explore the intricate task of incremental few-shot object detection in remote sensing images.
no code implementations • 15 May 2024 • Weijie L, Wei Yang, Yuenan Hou, Li Liu, Yongxiang Liu, Xiang Li
Various target characteristics, scene background information, and sensor parameters across ATR datasets challenge the generalization of those methods.
no code implementations • 15 May 2024 • Kai Hu, Weichen Yu, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Yining Li, Kai Chen, Zhiqiang Shen, Matt Fredrikson
Our approach relaxes the discrete jailbreak optimization into a continuous optimization and progressively increases the sparsity of the optimizing vectors.
1 code implementation • 12 May 2024 • Xiang Li, Jian Song, Zhigang Zhao, Chunxiao Wang, Dawei Song, Bin Hu
This study introduces a novel Supervised Info-enhanced Contrastive Learning framework for EEG based Emotion Recognition (SICLEER).
no code implementations • 29 Apr 2024 • Xiang Li, Zhi-Qi Cheng, Jun-Yan He, Xiaojiang Peng, Alexander G. Hauptmann
Emotional Text-to-Speech (E-TTS) synthesis has gained significant attention in recent years due to its potential to enhance human-computer interaction.
no code implementations • 26 Apr 2024 • Xiang Li, Hu Yang
(2) In multivariate non-stationary series prediction, DeepVARMA uses a phased processing strategy to show higher adaptability and accuracy compared to the traditional VARMA model as well as the machine learning models LSTM, RF and XGBoost.
no code implementations • 25 Apr 2024 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Chao Wang, Xinzhang Liu, Zihan Wang, Yu Zhao, Xin Wang, Yuyao Huang, Shuangyong Song, Yongxiang Li, Zheng Zhang, Bo Zhao, Aixin Sun, Yequan Wang, Zhongjiang He, Zhongyuan Wang, Xuelong Li, Tiejun Huang
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications.
no code implementations • 18 Apr 2024 • Xiang Li, Shunpan Liang, Yu Lei, Chen Li, Yulei Hou, Tengfei Ma
Medication recommendation systems are designed to deliver personalized drug suggestions that are closely aligned with individual patient needs.
no code implementations • 17 Apr 2024 • Long Cao, Liwei Ge, Daochi Zhang, Xiang Li, Yao Wang, Rui-Xue Xu, YiJing Yan, Xiao Zheng
Simulating the dynamics of open quantum systems coupled to non-Markovian environments remains an outstanding challenge due to exponentially scaling computational costs.
no code implementations • 11 Apr 2024 • Jiayi Wu, Renyu Zhu, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao
Over the past few years, we have witnessed remarkable advancements in Code Pre-trained Models (CodePTMs).
no code implementations • 10 Apr 2024 • Shangyu Chen, Zibo Zhao, YuanYuan Zhao, Xiang Li
Besides, we proposed a series of evaluation protocols for personalization: to what extend the response is personal to the different users.
no code implementations • 9 Apr 2024 • Sekeun Kim, Hui Ren, Peng Guo, Abder-Rahman Ali, Patrick Zhang, Kyungsang Kim, Xiang Li, Quanzheng Li
Echocardiography segmentation for cardiac analysis is time-consuming and resource-intensive due to the variability in image quality and the necessity to process scans from various standard views.
1 code implementation • 5 Apr 2024 • JunHao Chen, Xiang Li, Xiaojun Ye, Chao Li, Zhaoxin Fan, Hao Zhao
The definition of an IDEA is the composition of multimodal inputs including text, image, and 3D models.
no code implementations • 1 Apr 2024 • Xiang Li, Feng Ruan, Huiyuan Wang, Qi Long, Weijie J. Su
In particular, we derive optimal detection rules for these watermarks under our framework.
1 code implementation • 31 Mar 2024 • Xiang Li, Fan Bu, Ambuj Mehrish, Yingting Li, Jiale Han, Bo Cheng, Soujanya Poria
The pursuit of modern models, like Diffusion Models (DMs), holds promise for achieving high-fidelity, real-time speech synthesis.
1 code implementation • 25 Mar 2024 • Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya, Michael S. Ryoo
In addition to faster inference, we discover the resulting models to yield surprisingly good accuracy on long-video tasks, even with no video specific information.
1 code implementation • 21 Mar 2024 • Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, Qipeng Guo, Xipeng Qiu, Pengcheng Yin, XiaoLi Li, Fei Yuan, Lingpeng Kong, Xiang Li, Zhiyong Wu
Building on our examination of the developmental trajectories, we further investigate the emerging synergies between code intelligence and broader machine intelligence, uncovering new cross-domain opportunities and illustrating the substantial influence of code intelligence across various domains.
no code implementations • 20 Mar 2024 • Jiawei Zhou, Wuzhou Li, Yi Cao, Hongtao Cai, Xiang Li
Few-shot object detection (FSOD) has garnered significant research attention in the field of remote sensing due to its ability to reduce the dependency on large amounts of annotated data.
1 code implementation • 19 Mar 2024 • Chong Ma, Hanqi Jiang, WenTing Chen, Zihao Wu, Xiaowei Yu, Fang Zeng, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li
Additionally, we explore the impact of varying amounts of eye-gaze data on model performance, highlighting the feasibility and utility of integrating this auxiliary data into multi-modal pre-training.
1 code implementation • 19 Mar 2024 • Xiang Li, Zhenyu Li, Chen Shi, Yong Xu, Qing Du, Mingkui Tan, Jun Huang, Wei Lin
The task of financial analysis primarily encompasses two key areas: stock trend prediction and the corresponding financial question answering.
no code implementations • 19 Mar 2024 • Zhichao Feng, Junjiie Xie, Kaiyuan Li, Yu Qin, Pengfei Wang, Qianzhong Li, Bin Yin, Xiang Li, Wei Lin, Shangguang Wang
We first identify contexts that share similar user preferences with the target context and then locate the corresponding PoIs based on these identified contexts.
no code implementations • 18 Mar 2024 • Xiang Li, Chaofan Fu, Zhongying Zhao, Guanjie Zheng, Chao Huang, Junyu Dong, Yanwei Yu
Nevertheless, these approaches still grapple with two significant shortcomings: (1) Insufficient modeling and exploitation of the impact of various behavior patterns formed by multiplex relations between users and items on representation learning, and (2) ignoring the effect of different relations in the behavior patterns on the target relation in recommender system scenarios.
no code implementations • 18 Mar 2024 • Yizheng Wang, Xiang Li, Ziming Yan, Yuqing Du, Jinshuai Bai, Bokai Liu, Timon Rabczuk, Yinghua Liu
Homogenization is an essential tool for studying multiscale physical phenomena.
1 code implementation • 18 Mar 2024 • YuXuan Li, Xiang Li, Yimain Dai, Qibin Hou, Li Liu, Yongxiang Liu, Ming-Ming Cheng, Jian Yang
While a considerable amount of research has been dedicated to remote sensing classification, object detection and semantic segmentation, most of these studies have overlooked the valuable prior knowledge embedded within remote sensing scenarios.
no code implementations • 15 Mar 2024 • Zhennong Chen, Sekeun Kim, Hui Ren, Quanzheng Li, Xiang Li
Accurate 2D+T myocardium segmentation in cine cardiac magnetic resonance (CMR) scans is essential to analyze LV motion throughout the cardiac cycle comprehensively.
no code implementations • 15 Mar 2024 • Yongquan He, Xuancheng Huang, Minghao Tang, Lingxun Meng, Xiang Li, Wei Lin, Wenyuan Zhang, Yifu Gao
Recent methods try to alleviate the CF problem by modifying models or replaying data, which may only remember the surface-level pattern of instructions and get confused on held-out tasks.
1 code implementation • 13 Mar 2024 • Yupeng Zheng, Xiang Li, Pengfei Li, Yuhang Zheng, Bu Jin, Chengliang Zhong, Xiaoxiao Long, Hao Zhao, Qichao Zhang
However, existing methods rely on a complex cascaded framework with relatively limited information to restore 3D scenes, including a dependency on supervision solely on the whole network's output, single-frame input, and the utilization of a small backbone.
no code implementations • 12 Mar 2024 • Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren, Wenxuan Liu, Miao Su, Yucan Guo, Yantao Liu, Xiang Li, Zhilei Hu, Long Bai, Wei Li, Yidan Liu, Pan Yang, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
After instruction tuning, KnowCoder further exhibits strong generalization ability on unseen schemas and achieves up to $\textbf{12. 5%}$ and $\textbf{21. 9%}$, compared to sota baselines, under the zero-shot setting and the low resource setting, respectively.
no code implementations • 11 Mar 2024 • Qing Xiao, Siyeop Yoon, Hui Ren, Matthew Tivnan, Lichao Sun, Quanzheng Li, Tianming Liu, Yu Zhang, Xiang Li
Alzheimer's Disease (AD) is a neurodegenerative condition characterized by diverse progression rates among individuals, with changes in cortical thickness (CTh) closely linked to its progression.
1 code implementation • 11 Mar 2024 • YuXuan Li, Xiang Li, Weijie Li, Qibin Hou, Li Liu, Ming-Ming Cheng, Jian Yang
To the best of our knowledge, SARDet-100K is the first COCO-level large-scale multi-class SAR object detection dataset ever created.
Ranked #1 on 2D Object Detection on SARDet-100K (using extra training data)
no code implementations • 11 Mar 2024 • WenTing Chen, Pengyu Wang, Hui Ren, Lichao Sun, Quanzheng Li, Yixuan Yuan, Xiang Li
To address these challenges, we propose a novel medical image synthesis model that leverages fine-grained image-text alignment and anatomy-pathology prompts to generate highly detailed and accurate synthetic medical images.
no code implementations • 10 Mar 2024 • Xiang Li, Soo Min Kwon, Ismail R. Alkhouri, Saiprasad Ravishankar, Qing Qu
To solve image restoration problems, many existing techniques achieve data consistency by incorporating additional likelihood gradient steps into the reverse sampling process of diffusion models.
2 code implementations • 7 Mar 2024 • Xiang Li, Kai Qiu, Jinglu Wang, Xiaohao Xu, Rita Singh, Kashu Yamazak, Hao Chen, Xiaonan Huang, Bhiksha Raj
Referring perception, which aims at grounding visual objects with multimodal referring guidance, is essential for bridging the gap between humans, who provide instructions, and the environment where intelligent systems perceive.
no code implementations • 6 Mar 2024 • Di Zhang, Moyang Wang, Joseph Mango, Xiang Li, Xianrui Xu
Given these advancements, there has been a surge in novel methods employing reinforcement learning to tackle spatial resource allocation problems.
1 code implementation • 5 Mar 2024 • Zheng Li, Xiang Li, Xinyi Fu, Xin Zhang, Weiqiang Wang, Shuo Chen, Jian Yang
To our best knowledge, we are the first to (1) perform unsupervised domain-specific prompt-driven knowledge distillation for CLIP, and (2) establish a practical pre-storing mechanism of text features as shared class vectors between teacher and student.
Ranked #1 on Prompt Engineering on Oxford-IIIT Pet Dataset
no code implementations • 4 Mar 2024 • Siqi Fan, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang, Zhongyuan Wang
To answer this question, we first indicate that Not all Layers are Necessary during Inference by statistically analyzing the activated layers across tasks.
1 code implementation • 4 Mar 2024 • Lizhou Fan, Wenyue Hua, Xiang Li, Kaijie Zhu, Mingyu Jin, Lingyao Li, Haoyang Ling, Jinkui Chi, Jindong Wang, Xin Ma, Yongfeng Zhang
Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is an important area of research.
no code implementations • 1 Mar 2024 • Shunpan Liang, Xiang Li, Chen Li, Yu Lei, Yulei Hou, Tengfei Ma
Medication recommendation aims to integrate patients' long-term health records with medical knowledge, recommending accuracy and safe medication combinations for specific conditions.
1 code implementation • 28 Feb 2024 • Zhe Wang, Jianping Wu, Mengjun Zheng, Chenchen Geng, Borui Zhen, Wei zhang, Hui Wu, Zhengyang Xu, Gang Xu, Si Chen, Xiang Li
Many tools exist for extracting structural and physiochemical descriptors from linear peptides to predict their properties, but similar tools for hydrocarbon-stapled peptides are lacking. Here, we present StaPep, a Python-based toolkit designed for generating 2D/3D structures and calculating 21 distinct features for hydrocarbon-stapled peptides. The current version supports hydrocarbon-stapled peptides containing 2 non-standard amino acids (norleucine and 2-aminoisobutyric acid) and 6 nonnatural anchoring residues (S3, S5, S8, R3, R5 and R8). Then we established a hand-curated dataset of 201 hydrocarbon-stapled peptides and 384 linear peptides with sequence information and experimental membrane permeability, to showcase StaPep's application in artificial intelligence projects. A machine learning-based predictor utilizing above calculated features was developed with AUC of 0. 85, for identifying cell-penetrating hydrocarbon-stapled peptides. StaPep's pipeline spans data retrieval, cleaning, structure generation, molecular feature calculation, and machine learning model construction for hydrocarbon-stapled peptides. The source codes and dataset are freely available on Github: https://github. com/dahuilangda/stapep_package.
1 code implementation • 23 Feb 2024 • Ziheng Jiang, Haibin Lin, Yinmin Zhong, Qi Huang, Yangrui Chen, Zhi Zhang, Yanghua Peng, Xiang Li, Cong Xie, Shibiao Nong, Yulu Jia, Sun He, Hongmin Chen, Zhihao Bai, Qi Hou, Shipeng Yan, Ding Zhou, Yiyao Sheng, Zhuo Jiang, Haohan Xu, Haoran Wei, Zhang Zhang, Pengfei Nie, Leqi Zou, Sida Zhao, Liang Xiang, Zherui Liu, Zhe Li, Xiaoying Jia, Jianxi Ye, Xin Jin, Xin Liu
Training LLMs at this scale brings unprecedented challenges to training efficiency and stability.
no code implementations • 20 Feb 2024 • Penghai Zhao, Xin Zhang, Ming-Ming Cheng, Jian Yang, Xiang Li
To improve efficiency, this paper aims to provide a thorough review of reviews in the PAMI field from diverse perspectives.
1 code implementation • 20 Feb 2024 • Xiang Li, Yunshi Lan, Chao Yang
Recently, numerous new benchmarks have been established to evaluate the performance of large language models (LLMs) via either computing a holistic score or employing another LLM as a judge.
no code implementations • 18 Feb 2024 • Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, Huaxiu Yao
Recent advancements in large language models (LLMs) have shown promise in multi-step reasoning tasks, yet their reliance on extensive manual labeling to provide procedural feedback remains a significant impediment.
no code implementations • 18 Feb 2024 • Yucheng Zhou, Xiang Li, Qianning Wang, Jianbing Shen
In Large Visual Language Models (LVLMs), the efficacy of In-Context Learning (ICL) remains limited by challenges in cross-modal interactions and representation disparities.
no code implementations • 17 Feb 2024 • Shaochen Xu, Zihao Wu, Huaqin Zhao, Peng Shu, Zhengliang Liu, Wenxiong Liao, Sheng Li, Andrea Sikora, Tianming Liu, Xiang Li
In this study, we leverage LLM to enhance the semantic analysis and develop similarity metrics for texts, addressing the limitations of traditional unsupervised NLP metrics like ROUGE and BLEU.
no code implementations • 16 Feb 2024 • Muqiao Yang, Xiang Li, Umberto Cappellazzo, Shinji Watanabe, Bhiksha Raj
In this work, we propose an evaluation methodology that provides a unified evaluation on stability, plasticity, and generalizability in continual learning.
no code implementations • 15 Feb 2024 • Chengcheng Yu, Jiapeng Zhu, Xiang Li
It learns an optimal policy to acquire class-balanced and informative nodes for annotation, maximizing the performance of GNNs trained with selected labeled nodes.
1 code implementation • 12 Feb 2024 • Xiaohao Xu, Tianyi Zhang, Sibo Wang, Xiang Li, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Xiaonan Huang
To this end, we propose a novel, customizable pipeline for noisy data synthesis, aimed at assessing the resilience of multi-modal SLAM models against various perturbations.
1 code implementation • 2 Feb 2024 • Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj
Weakly supervised learning generally faces challenges in applicability to various scenarios with diverse weak supervision and in scalability due to the complexity of existing algorithms, thereby hindering the practical deployment.
no code implementations • 26 Jan 2024 • Yipin Lei, Xu Wang, Meng Fang, Han Li, Xiang Li, Jianyang Zeng
In summary, our proposed frameworks can serve as potent tools to facilitate peptide early drug discovery.
1 code implementation • 19 Jan 2024 • Zhengliang Liu, Jason Holmes, Wenxiong Liao, Chenbin Liu, Lian Zhang, Hongying Feng, Peilong Wang, Muhammad Ali Elahi, Hongmin Cai, Lichao Sun, Quanzheng Li, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu
ROND is specifically designed to address this gap in the domain of radiation oncology, a field that offers many opportunities for NLP exploration.
1 code implementation • 18 Jan 2024 • Xianfu Cheng, Weixiao Zhou, Xiang Li, Xiaoming Chen, Jian Yang, Tongliang Li, Zhoujun Li
In this work, we propose the VIsion Permutable extractor for fast and efficient scene Text Recognition (VIPTR), which achieves an impressive balance between high performance and rapid inference speeds in the domain of STR.
1 code implementation • 18 Jan 2024 • Chenghua Gong, Yao Cheng, Xiang Li, Caihua Shan, Siqiang Luo
Graphs are structured data that models complex relations between real-world entities.
1 code implementation • 10 Jan 2024 • Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric Xing, Furong Huang, Hao liu, Heng Ji, Hongyi Wang, huan zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao
This paper introduces TrustLLM, a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions.
2 code implementations • 10 Jan 2024 • Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, Yunxin Liu
Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.
no code implementations • 9 Jan 2024 • Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, Xuhui Wang, Yincheng Yao, Xuan Liu, Huaqin Zhao, Zhengliang Liu, Haixing Dai, Lin Zhao, Bao Ge, Xiang Li, Tianming Liu, Shu Zhang
Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.
no code implementations • 8 Jan 2024 • Yuze Han, Xiang Li, Zhihua Zhang
In two-time-scale stochastic approximation (SA), two iterates are updated at varying speeds using different step sizes, with each update influencing the other.
no code implementations • 1 Jan 2024 • Xiang Li, Kevin M. Short
Through experiments on image datasets such as MNIST, we show that we can use null space components to force the neural network to choose a selected hidden image class, even though the overall image can be made to look like a completely different image.
no code implementations • 27 Dec 2023 • Shijian Jiang, Qi Ye, Rengan Xie, Yuchi Huo, Xiang Li, Yang Zhou, Jiming Chen
We evaluate our approach on HO3D and HOD datasets and demonstrate that it outperforms the state-of-the-art methods in terms of reconstruction surface quality, with an improvement of $52\%$ on HO3D and $20\%$ on HOD.
no code implementations • 13 Dec 2023 • WenTing Chen, Linlin Shen, Xiang Li, Yixuan Yuan
To address these issues, we propose a novel Adaptive patch-word Matching (AdaMatch) model to correlate chest X-ray (CXR) image regions with words in medical reports and apply it to CXR-report generation to provide explainability for the generation process.
1 code implementation • 12 Dec 2023 • Xiang Li, Haoran Tang, Siyu Chen, Ziwei Wang, Anurag Maravi, Marcin Abram
In this paper, we explore the challenges inherent to Large Language Models (LLMs) like GPT-4, particularly their propensity for hallucinations, logic mistakes, and incorrect conclusions when tasked with answering complex questions.
no code implementations • 6 Dec 2023 • Ryan Burgert, Xiang Li, Abe Leite, Kanchana Ranasinghe, Michael S. Ryoo
We explore the problem of computationally generating special `prime' images that produce optical illusions when physically arranged and viewed in a certain way.
no code implementations • 5 Dec 2023 • Xiang Li, Jian Ding, Zhaoyang Chen, Mohamed Elhoseiny
In this work, we present Uni3DL, a unified model for 3D and Language understanding.
no code implementations • 4 Dec 2023 • Byung-Hoon Kim, JungWon Choi, Eunggu Yun, Kyungsang Kim, Xiang Li, Juho Lee
Here, we propose a method for learning the representation of dynamic functional connectivity with Graph Transformers.
1 code implementation • 29 Nov 2023 • Xiang Li, Qianli Shen, Kenji Kawaguchi
The booming use of text-to-image generative models has raised concerns about their high risk of producing copyright-infringing content.
no code implementations • 27 Nov 2023 • Xiang Li, Long Lan, Husam Lahza, Shaowu Yang, Shuihua Wang, Wenjing Yang, Hengzhu Liu, Yudong Zhang
EAFP-Med can efficiently extract lesion features from various medical images based on prompts, enhancing the model's performance.
1 code implementation • 22 Nov 2023 • JunHao Chen, Peng Rong, Jingbo Sun, Chao Li, Xiang Li, Hongwu Lv
We introduce a large language model to parse the text and identify stylization goals and specific styles.
1 code implementation • 21 Nov 2023 • Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao
We theoretically show that the consensus mechanism can guarantee the convergence of the global objective.
no code implementations • 15 Nov 2023 • Xiang Li, Che Wang, Bing Li, Hao Chen, Sizhe Li
In this paper, we propose a method for knowledge graph construction in power distribution networks.
1 code implementation • 15 Nov 2023 • Yunshi Lan, Xiang Li, Xin Liu, Yang Li, Wei Qin, Weining Qian
This results in a set of candidate answers.
no code implementations • 15 Nov 2023 • Yuanwei Wu, Xiang Li, Yixin Liu, Pan Zhou, Lichao Sun
This finding indicates potential exploitable security risks in MLLMs; 2) Based on the acquired system prompts, we propose a novel MLLM jailbreaking attack method termed SASP (Self-Adversarial Attack via System Prompt).
no code implementations • 14 Nov 2023 • Yige Zhao, Jianxiang Yu, Yao Cheng, Chengcheng Yu, Yiding Liu, Xiang Li, Shuaiqiang Wang
Instead of directly reconstructing raw features for attributed nodes, SHAVA generates the initial low-dimensional representation matrix for all the nodes, based on which raw features of attributed nodes are further reconstructed to leverage accurate attributes.
no code implementations • 10 Nov 2023 • Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, Chao Cao, Zhenxiang Xiao, Jiaqi Wang, Huan Zhao, Shaochen Xu, Yaonai Wei, Jingyuan Chen, Haixing Dai, Peilong Wang, Hao He, Zewei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yiheng Liu, Kai Zhang, Liheng Yan, Lichao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xintao Hu, Yixuan Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quanzheng Li, Wei Liu, Xiang Li, Dajiang Zhu, Tianming Liu
GPT-4V represents a breakthrough in artificial general intelligence (AGI) for computer vision, with applications in the biomedical domain.
1 code implementation • 9 Nov 2023 • Jinjin Xu, Liwu Xu, Yuzhe Yang, Xiang Li, Fanyi Wang, Yanchun Xie, Yi-Jie Huang, Yaqian Li
Recent advancements in multi-modal large language models (MLLMs) have led to substantial improvements in visual understanding, primarily driven by sophisticated modality alignment strategies.
no code implementations • 7 Nov 2023 • Xiang Li, Xiangyu Zhou, Rui Dong, Yihong Zhang, Xinyu Wang
Our algorithm can reduce the space of programs with local variables.
1 code implementation • 7 Nov 2023 • Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, BingCheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
In this paper, we present the results of the NeurIPS-2022 Neural MMO Challenge, which attracted 500 participants and received over 1, 600 submissions.
no code implementations • 7 Nov 2023 • Mengge Liu, Wen Zhang, Xiang Li, Yanzhi Tian, Yuhang Guo, Jian Luan, Bin Wang, Shuoying Chen
Simultaneous machine translation (SiMT) is a challenging task that requires starting translation before the full source sentence is available.
no code implementations • 6 Nov 2023 • Siyi Zhang, Cheng Liu, Xiang Li, Xin Zhai, Zhen Wei, Sizhe Li, Xun Ma
The current trend of automating inspections at substations has sparked a surge in interest in the field of transformer image recognition.
no code implementations • 6 Nov 2023 • Yucan Guo, Zixuan Li, Xiaolong Jin, Yantao Liu, Yutao Zeng, Wenxuan Liu, Xiang Li, Pan Yang, Long Bai, Jiafeng Guo, Xueqi Cheng
Therefore, in this paper, we propose a universal retrieval-augmented code generation framework based on LLMs, called Code4UIE, for IE tasks.
no code implementations • 6 Nov 2023 • Yao Cheng, Minjie Chen, Xiang Li, Caihua Shan, Ming Gao
Specifically, the framework consists of three components: a backbone GNN model, a propagation controller to determine the optimal propagation steps for nodes, and a weight controller to compute the priority scores for nodes.
no code implementations • 6 Nov 2023 • Florian Hübler, Junchi Yang, Xiang Li, Niao He
However, as the assumption is relaxed to the more realistic $(L_0, L_1)$-smoothness, all existing convergence results still necessitate tuning of the stepsize.
no code implementations • 6 Nov 2023 • Zeyuan Zhao, Qingqing Ge, Anfeng Cheng, Yiding Liu, Xiang Li, Shuaiqiang Wang
In addition, most of them only consider the interactions between nodes while neglecting the high-order information behind the latent interactions among different node features.
no code implementations • 3 Nov 2023 • Qingqing Ge, Jianxiang Yu, Zeyuan Zhao, Xiang Li
To further leverage the information of clean labels in the noisy label set, we put forward LNP-v2, which incorporates the noisy label set into the Bayesian network to generate clean labels.
1 code implementation • 31 Oct 2023 • Srijan Das, Tanmay Jain, Dominick Reilly, Pranav Balaji, Soumyajit Karmakar, Shyam Marjit, Xiang Li, Abhijit Das, Michael S. Ryoo
We explore the appropriate SSL tasks that can be optimized alongside the primary task, the training schemes for these tasks, and the data scale at which they can be most effective.
1 code implementation • 29 Oct 2023 • Zhiling Yan, Kai Zhang, Rong Zhou, Lifang He, Xiang Li, Lichao Sun
In this paper, we critically evaluate the capabilities of the state-of-the-art multimodal large language model, i. e., GPT-4 with Vision (GPT-4V), on Visual Question Answering (VQA) task.
1 code implementation • 27 Oct 2023 • Habib Slim, Xiang Li, Yuchen Li, Mahmoud Ahmed, Mohamed Ayman, Ujjwal Upadhyay, Ahmed Abdelreheem, Arpit Prajapati, Suhail Pothigara, Peter Wonka, Mohamed Elhoseiny
In this work, we present 3DCoMPaT$^{++}$, a multimodal 2D/3D dataset with 160 million rendered views of more than 10 million stylized 3D shapes carefully annotated at the part-instance level, alongside matching RGB point clouds, 3D textured meshes, depth maps, and segmentation masks.
no code implementations • 26 Oct 2023 • Qingqing Ge, Zeyuan Zhao, Yiding Liu, Anfeng Cheng, Xiang Li, Shuaiqiang Wang, Dawei Yin
Graph Neural Networks (GNNs) are powerful in learning semantics of graph data.
no code implementations • 25 Oct 2023 • Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li
In this paper, we study graph label noise in the context of arbitrary heterophily, with the aim of rectifying noisy labels and assigning labels to previously unlabeled nodes.
1 code implementation • 20 Oct 2023 • Zhaohui Zheng, Yuming Chen, Qibin Hou, Xiang Li, Ping Wang, Ming-Ming Cheng
A fundamental limitation of object detectors is that they suffer from "spatial bias", and in particular perform less satisfactorily when detecting objects near image borders.
no code implementations • 20 Oct 2023 • Ze Gao, Xiang Li, Changkun Liu, Xian Wang, Anqi Wang, Liang Yang, Yuyang Wang, Pan Hui, Tristan Braud
We present VR PreM+, an innovative VR system designed to enhance web exploration beyond traditional computer screens.
1 code implementation • 19 Oct 2023 • Jianing Wang, Qiushi Sun, Nuo Chen, Chengyu Wang, Jun Huang, Ming Gao, Xiang Li
The recent success of large pre-trained language models (PLMs) heavily hinges on massive labeled data, which typically produces inferior performance in low-resource scenarios.
no code implementations • 16 Oct 2023 • Chenghua Gong, Xiang Li, Jianxiang Yu, Cheng Yao, Jiaqi Tan, Chengcheng Yu, Dawei Yin
Third, we design a prompting tuning method for our multi-view graph contrastive learning method to bridge the gap between pretexts and downsteam tasks.
no code implementations • 15 Oct 2023 • Jianxiang Yu, Yuxiang Ren, Chenghua Gong, Jiaqi Tan, Xiang Li, Xuecang Zhang
In order to tackle this challenge, we propose a lightweight paradigm called ENG, which adopts a plug-and-play approach to empower text-attributed graphs through node generation using LLMs.
1 code implementation • 15 Oct 2023 • Yueqi Ma, Minjie Chen, Xiang Li
Recently, Mixup has been introduced to synthesize hard negative samples in graph contrastive learning (GCL).
1 code implementation • 14 Oct 2023 • Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny
Motivated by this, we target to build a unified interface for completing many vision-language tasks including image description, visual question answering, and visual grounding, among others.
Ranked #10 on Visual Question Answering on BenchLMM
1 code implementation • 14 Oct 2023 • Zhihui Zhang, Jianxiang Yu, Xiang Li
Session-based recommendation (SBR) is a task that aims to predict items based on anonymous sequences of user behaviors in a session.
1 code implementation • 8 Oct 2023 • Chengcheng Han, Xiaowei Du, Che Zhang, Yixin Lian, Xiang Li, Ming Gao, Baoyuan Wang
Chain-of-Thought (CoT) prompting has proven to be effective in enhancing the reasoning capabilities of Large Language Models (LLMs) with at least 100 billion parameters.
no code implementations • 8 Oct 2023 • Tianyang Zhong, Wei Zhao, Yutong Zhang, Yi Pan, Peixin Dong, Zuowei Jiang, Xiaoyan Kui, Youlan Shang, Li Yang, Yaonai Wei, Longtao Yang, Hao Chen, Huan Zhao, Yuxiao Liu, Ning Zhu, Yiwei Li, Yisong Wang, Jiaqi Yao, Jiaqi Wang, Ying Zeng, Lei He, Chao Zheng, Zhixue Zhang, Ming Li, Zhengliang Liu, Haixing Dai, Zihao Wu, Lu Zhang, Shu Zhang, Xiaoyan Cai, Xintao Hu, Shijie Zhao, Xi Jiang, Xin Zhang, Xiang Li, Dajiang Zhu, Lei Guo, Dinggang Shen, Junwei Han, Tianming Liu, Jun Liu, Tuo Zhang
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels.
no code implementations • 3 Oct 2023 • Somya Sharma Chatterjee, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher Duffy, Vipin Kumar
Our inverse model offers 3\% improvement in R$^2$ for the inverse model (basin characteristic estimation) and 6\% for the forward model (streamflow prediction).
no code implementations • 1 Oct 2023 • Xiang Li, Yinpeng Chen, Chung-Ching Lin, Hao Chen, Kai Hu, Rita Singh, Bhiksha Raj, Lijuan Wang, Zicheng Liu
This paper presents a novel approach to object completion, with the primary goal of reconstructing a complete object from its partially visible components.
1 code implementation • 30 Sep 2023 • Qiushi Sun, Zhangyue Yin, Xiang Li, Zhiyong Wu, Xipeng Qiu, Lingpeng Kong
Large Language Models (LLMs) are evolving at an unprecedented pace and have exhibited considerable capability in the realm of natural language processing (NLP) with world knowledge.
3 code implementations • 29 Sep 2023 • Xiang Li, Jinglu Wang, Xiaohao Xu, Xiulian Peng, Rita Singh, Yan Lu, Bhiksha Raj
We propose a semantic decomposition method based on product quantization, where the multi-source semantics can be decomposed and represented by several disentangled and noise-suppressed single-source semantics.
no code implementations • 28 Sep 2023 • Manuel Schürch, Xiang Li, Ahmed Allam, Giulia Rathmes, Amina Mollaysa, Claudia Cavelti-Weder, Michael Krauthammer
We propose a novel framework that combines deep generative time series models with decision theory for generating personalized treatment strategies.
no code implementations • 27 Sep 2023 • Yucheng Shi, Shaochen Xu, Zhengliang Liu, Tianming Liu, Xiang Li, Ninghao Liu
Focusing on medical QA using the MedQA-SMILE dataset, we evaluate the impact of different retrieval models and the number of facts provided to the LLM.
no code implementations • 25 Sep 2023 • Jianwei Yu, Hangting Chen, Yanyao Bian, Xiang Li, Yi Luo, Jinchuan Tian, Mengyang Liu, Jiayi Jiang, Shuai Wang
To address this issue, we introduce an automatic in-the-wild speech data preprocessing framework (AutoPrep) in this paper, which is designed to enhance speech quality, generate speaker labels, and produce transcriptions automatically.
1 code implementation • 24 Sep 2023 • Sekeun Kim, Kyungsang Kim, Jiang Hu, Cheng Chen, Zhiliang Lyu, Ren Hui, Sunghwan Kim, Zhengliang Liu, Aoxiao Zhong, Xiang Li, Tianming Liu, Quanzheng Li
The Segmentation Anything Model (SAM) has gained significant attention for its robust generalization capabilities across diverse downstream tasks.
1 code implementation • 23 Sep 2023 • Xiang Li, JunHao Chen, Chao Li, Hongwu Lv
Audio recognition in specialized areas such as birdsong and submarine acoustics faces challenges in large-scale pre-training due to the limitations in available samples imposed by sampling environments and specificity requirements.
2 code implementations • 22 Sep 2023 • Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei
Diffusion models have gained prominence in the image domain for their capabilities in data generation and transformation, achieving state-of-the-art performance in various tasks in both image and audio domains.
no code implementations • 21 Sep 2023 • Xianhao Wei, Jia Jia, Xiang Li, Zhiyong Wu, Ziyi Wang
More interestingly, although we aim at the synthesis effect of the style transfer model, the synthesized speech by the proposed text prosodic analysis model is even better than the style transfer from the original speech in some user evaluation indicators.
no code implementations • 19 Sep 2023 • Chenhao Tang, Zhengliang Liu, Chong Ma, Zihao Wu, Yiwei Li, Wei Liu, Dajiang Zhu, Quanzheng Li, Xiang Li, Tianming Liu, Lei Fan
In this study, we investigate a privacy policy text analysis framework PolicyGPT based on the LLM.
no code implementations • 18 Sep 2023 • Zhengliang Liu, Peilong Wang, Yiwei Li, Jason Holmes, Peng Shu, Lian Zhang, Chenbin Liu, Ninghao Liu, Dajiang Zhu, Xiang Li, Quanzheng Li, Samir H. Patel, Terence T. Sio, Tianming Liu, Wei Liu
This paper presents RadOnc-GPT, a large language model specialized for radiation oncology through advanced tuning methods.
1 code implementation • 16 Sep 2023 • Cheng Chen, Juzheng Miao, Dufan Wu, Zhiling Yan, Sekeun Kim, Jiang Hu, Aoxiao Zhong, Zhengliang Liu, Lichao Sun, Xiang Li, Tianming Liu, Pheng-Ann Heng, Quanzheng Li
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation tasks.
no code implementations • 14 Sep 2023 • Sipan Li, Songxiang Liu, Luwen Zhang, Xiang Li, Yanyao Bian, Chao Weng, Zhiyong Wu, Helen Meng
However, it is still challenging to train a universal vocoder which can generalize well to out-of-domain (OOD) scenarios, such as unseen speaking styles, non-speech vocalization, singing, and musical pieces.
no code implementations • 11 Sep 2023 • Li Du, Yequan Wang, Xingrun Xing, Yiqun Ya, Xiang Li, Xin Jiang, Xuezhi Fang
Although demonstrating superb performance on various NLP tasks, large language models (LLMs) still suffer from the hallucination problem, which threatens the reliability of LLMs.
no code implementations • 7 Sep 2023 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Xuying Meng, Siqi Fan, Peng Han, Jing Li, Li Du, Bowen Qin, Zheng Zhang, Aixin Sun, Yequan Wang
We demonstrate that a 101B-parameter LLM with 0. 31T tokens can be trained with a budget of 100K US dollars.
1 code implementation • 5 Sep 2023 • Renyu Zhu, Chengcheng Han, Yong Qian, Qiushi Sun, Xiang Li, Ming Gao, Xuezhi Cao, Yunsen Xian
To solve these issues, in this paper, we propose a novel exchanging-based multimodal fusion model MuSE for text-vision fusion based on Transformer.
no code implementations • 5 Sep 2023 • Minjie Chen, Yao Cheng, Ye Wang, Xiang Li, Ming Gao
Further, Since the triplet loss only optimizes the relative distance between the anchor and its positive/negative samples, it is difficult to ensure the absolute distance between the anchor and positive sample.
no code implementations • 1 Sep 2023 • Zhiqiang Yan, Xiang Li, Le Hui, Zhenyu Zhang, Jun Li, Jian Yang
To tackle these challenges, we explore a repetitive design in our image guided network to gradually and sufficiently recover depth values.
no code implementations • 31 Aug 2023 • Xiang Li, Shunpan Liang, Yulei Hou, Tengfei Ma
After that, we design a pyramid-like stratification method based on relevance to strengthen the expressiveness of sparse data.
no code implementations • 31 Aug 2023 • Xiang Li, Juncheng Guo, Qige Song, Jiang Xie, Yafei Sang, Shuyuan Zhao, Yongzheng Zhang
Despite some existing learning-based ETC methods showing promising results, three-fold limitations still remain in real-world network environments, 1) label bias caused by traffic class imbalance, 2) traffic homogeneity caused by component sharing, and 3) training with reliance on sufficient labeled traffic.
no code implementations • 29 Aug 2023 • Zhengliang Liu, Yiwei Li, Peng Shu, Aoxiao Zhong, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Jie Luo, Cheng Chen, Sekeun Kim, Jiang Hu, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Tianming Liu, Quanzheng Li, Xiang Li
This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning.
1 code implementation • 28 Aug 2023 • Jinliang Yuan, Chen Yang, Dongqi Cai, Shihe Wang, Xin Yuan, Zeling Zhang, Xiang Li, Dingge Zhang, Hanzi Mei, Xianqing Jia, Shangguang Wang, Mengwei Xu
Concurrently, each app contributes a concise, offline fine-tuned "adapter" tailored to distinct downstream tasks.
1 code implementation • 26 Aug 2023 • Mengwei Xu, Dongqi Cai, Yaozong Wu, Xiang Li, Shangguang Wang
Federated Learning (FL), a method to preserve user data privacy, is often employed in fine-tuning LLMs to downstream mobile tasks, an approach known as FedLLM.
2 code implementations • 25 Aug 2023 • Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao
This paper presents a self-supervised framework to demonstrate the feasibility of learning image representations from EEG signals, particularly for object recognition.
2 code implementations • ICCV 2023 • Lingyu Xiao, Xiang Li, Sen yang, Wankou Yang
In this paper, we revisit the limitations of anchor-based lane detection methods, which have predominantly focused on fixed anchors that stem from the edges of the image, disregarding their versatility and quality.
no code implementations • 19 Aug 2023 • Kun Wang, Zhiqiang Yan, Huang Tian, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang
Neural Radiance Fields (NeRF) have shown promise in generating realistic novel views from sparse scene images.
no code implementations • 14 Aug 2023 • Xiang Li, Songcan Chen
Then, by using the prior of degrees, we design a weighted scheme and verify its effectiveness.
no code implementations • 9 Aug 2023 • Shuwei Chen, Xiang Li, Jian Dong, Jin Zhang, Yongkang Wang, Xingxing Wang
Click-through rate (CTR) prediction plays a pivotal role in the success of recommendations.
no code implementations • 7 Aug 2023 • Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, Wei Lin
The analysis and mining of user heterogeneous behavior are of paramount importance in recommendation systems.
no code implementations • 31 Jul 2023 • Jia Li, Xiang Li
Observation-Oriented paradigm currently dominates relationship learning models, including AI-based ones, which inherently do not account for relationships with temporally nonlinear effects.
no code implementations • 29 Jul 2023 • Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao
To address this challenge, we extend the adaptive risk minimization technique into the unsupervised personalized federated learning setting and propose our method, FedTTA.
1 code implementation • 29 Jul 2023 • Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao
The resistance of pFL methods with parameter decoupling is attributed to the heterogeneous classifiers between malicious clients and benign counterparts.
no code implementations • 29 Jul 2023 • Mengyi Yuan, Minjie Chen, Xiang Li
Finally, an alternating training scheme is adopted to ensure that unsupervised node representation learning and information fusion controller can mutually reinforce each other.
1 code implementation • 28 Jul 2023 • Yuan Hu, Jianlong Yuan, Congcong Wen, Xiaonan Lu, Xiang Li
This dataset consists of human-annotated captions and visual question-answer pairs, allowing for a comprehensive assessment of VLMs in the context of RS.
1 code implementation • 26 Jul 2023 • Liao Qu, Xianwei Zou, Xiang Li, Yandong Wen, Rita Singh, Bhiksha Raj
This work unveils the enigmatic link between phonemes and facial features.
no code implementations • 26 Jul 2023 • Xiang Li, Yandong Wen, Muqiao Yang, Jinglu Wang, Rita Singh, Bhiksha Raj
Previous works on voice-face matching and voice-guided face synthesis demonstrate strong correlations between voice and face, but mainly rely on coarse semantic cues such as gender, age, and emotion.
2 code implementations • ICCV 2023 • Renke Wang, Guimin Que, Shuo Chen, Xiang Li, Jun Li, Jian Yang
Our focus lies primarily on birds, a popular subject in 3D reconstruction, for which no existing single-view 3D transfer methods have been developed. The method we propose seeks to generate a 3D mesh shape and texture of a bird from two single-view images.
1 code implementation • 25 Jul 2023 • Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, Peng Shu, Yaonai Wei, Zihao Wu, Chong Ma, Jiaqi Wang, Sheng Wang, Mengyue Zhou, Zuowei Jiang, Chunlin Li, Jason Holmes, Shaochen Xu, Lu Zhang, Haixing Dai, Kai Zhang, Lin Zhao, Yuanhao Chen, Xu Liu, Peilong Wang, Pingkun Yan, Jun Liu, Bao Ge, Lichao Sun, Dajiang Zhu, Xiang Li, Wei Liu, Xiaoyan Cai, Xintao Hu, Xi Jiang, Shu Zhang, Xin Zhang, Tuo Zhang, Shijie Zhao, Quanzheng Li, Hongtu Zhu, Dinggang Shen, Tianming Liu
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP).
no code implementations • 21 Jul 2023 • Zihan Guan, Zihao Wu, Zhengliang Liu, Dufan Wu, Hui Ren, Quanzheng Li, Xiang Li, Ninghao Liu
Participant recruitment based on unstructured medical texts such as clinical notes and radiology reports has been a challenging yet important task for the cohort establishment in clinical research.
no code implementations • 17 Jul 2023 • Liangyu Zha, Junlin Zhou, Liyao Li, Rui Wang, Qingyi Huang, Saisai Yang, Jing Yuan, Changbao Su, Xiang Li, Aofeng Su, Tao Zhang, Chen Zhou, Kaizhe Shou, Miao Wang, Wufang Zhu, Guoshan Lu, Chao Ye, Yali Ye, Wentao Ye, Yiming Zhang, Xinglong Deng, Jie Xu, Haobo Wang, Gang Chen, Junbo Zhao
Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate.
2 code implementations • 17 Jul 2023 • Ruichen Li, Haotian Ye, Du Jiang, Xuelan Wen, Chuwei Wang, Zhe Li, Xiang Li, Di He, Ji Chen, Weiluo Ren, LiWei Wang
Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry.
1 code implementation • 5 Jul 2023 • Hongmin Cai, Xiaoke Huang, Zhengliang Liu, Wenxiong Liao, Haixing Dai, Zihao Wu, Dajiang Zhu, Hui Ren, Quanzheng Li, Tianming Liu, Xiang Li
As AD impairs the patient's language understanding and expression ability, the speech of AD patients can serve as an indicator of this disease.
1 code implementation • 4 Jul 2023 • Xiang Li, Varun Belagali, Jinghuan Shang, Michael S. Ryoo
Sequence modeling approaches have shown promising results in robot imitation learning.
1 code implementation • 3 Jul 2023 • Haixing Dai, Chong Ma, Zhiling Yan, Zhengliang Liu, Enze Shi, Yiwei Li, Peng Shu, Xiaozheng Wei, Lin Zhao, Zihao Wu, Fang Zeng, Dajiang Zhu, Wei Liu, Quanzheng Li, Lichao Sun, Shu Zhang Tianming Liu, Xiang Li
Starting with an initial point prompt, SAM produces an initial mask, which is then fed into our proposed SAMAug to generate augmented point prompts.
no code implementations • 3 Jul 2023 • Haixing Dai, Mengxuan Hu, Qing Li, Lu Zhang, Lin Zhao, Dajiang Zhu, Ibai Diez, Jorge Sepulcre, Fan Zhang, Xingyu Gao, Manhua Liu, Quanzheng Li, Sheng Li, Tianming Liu, Xiang Li
Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition.
no code implementations • 3 Jul 2023 • Jiaqi Wang, Zhengliang Liu, Lin Zhao, Zihao Wu, Chong Ma, Sigang Yu, Haixing Dai, Qiushi Yang, Yiheng Liu, Songyao Zhang, Enze Shi, Yi Pan, Tuo Zhang, Dajiang Zhu, Xiang Li, Xi Jiang, Bao Ge, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang
This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering.
no code implementations • 27 Jun 2023 • Yang Qiao, Yiping Xia, Xiang Li, Zheng Li, Yan Ge
H-GAT is able to capture higher-order structures and jointly incorporate factors of fundamental analysis with factors of technical analysis.
no code implementations • 27 Jun 2023 • Xiao Guo, Xiang Li, Xiangyu Chang, Shujie Ma
To remove the bias incurred by RR and the squared network matrices, we develop a two-step bias-adjustment procedure.
1 code implementation • 20 Jun 2023 • Jiabao Wang, Yuming Chen, Zhaohui Zheng, Xiang Li, Ming-Ming Cheng, Qibin Hou
Moreover, as mimicking the teacher's predictions is the target of KD, CrossKD offers more task-oriented information in contrast with feature imitation.
no code implementations • 20 Jun 2023 • Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, Dajiang Zhu, Tianming Liu, Wei Liu
Given that SAM, a model pre-trained purely on natural images, can handle the delineation of OARs from medical images with clinically acceptable accuracy, these results highlight SAM's robust generalization capabilities with consistent accuracy in automatic segmentation for radiotherapy.
no code implementations • 16 Jun 2023 • Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, Xiaobai Yao, Lu Shi, Quanzheng Li, Zhuo Chen, Donglan Zhang, Gengchen Mai, Tianming Liu
In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which can conduct data collection, processing, and analysis about complex health narratives of Alzheimer's Disease in an autonomous manner via users' textual prompts.
no code implementations • 15 Jun 2023 • Rohit Paturi, Sundararajan Srinivasan, Xiang Li
Speaker diarization (SD) is typically used with an automatic speech recognition (ASR) system to ascribe speaker labels to recognized words.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 14 Jun 2023 • Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Lichao Sun, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Xiang Li, Quanzheng Li, Tianming Liu
We introduce Radiology-GPT, a large language model for radiology.
no code implementations • 12 Jun 2023 • Yu Zhang, Jia Li, Jie Ding, Xiang Li
Learning and analysis of network robustness, including controllability robustness and connectivity robustness, is critical for various networked systems against attacks.
no code implementations • 12 Jun 2023 • Xiang Li, Haocheng Xia, Jinfei Liu
Data valuation has become an increasingly significant discipline in data science due to the economic value of data.
no code implementations • 10 Jun 2023 • Jianing Wang, Qiushi Sun, Nuo Chen, Xiang Li, Ming Gao
To mitigate this brittleness, we propose a novel Chain-of-Knowledge (CoK) prompting, where we aim at eliciting LLMs to generate explicit pieces of knowledge evidence in the form of structure triple.
no code implementations • 8 Jun 2023 • Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen
In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare, focusing on foundational Large Language Models (LLMs), Large Vision Models, and Large Multimodal Models.
no code implementations • 8 Jun 2023 • Kun Wang, Zhiqiang Yan, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang
Our key contributions are: (1) We parameterize the geometry and appearance of the object using a multi-scale global feature extractor, which avoids frequent point-wise feature retrieval and camera dependency.
1 code implementation • NeurIPS 2023 • Lingfeng Yang, Yueze Wang, Xiang Li, Xinlong Wang, Jian Yang
Previous works have suggested that incorporating visual prompts, such as colorful boxes or circles, can improve the ability of models to recognize objects of interest.
1 code implementation • 7 Jun 2023 • Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu
Different from traditional recommendation, takeaway recommendation faces two main challenges: (1) Dual Interaction-Aware Preference Modeling.
1 code implementation • 30 May 2023 • Xiang Li, Chung-Ching Lin, Yinpeng Chen, Zicheng Liu, Jinglu Wang, Bhiksha Raj
The paper introduces PaintSeg, a new unsupervised method for segmenting objects without any training.
1 code implementation • 27 May 2023 • Zhibin Lan, Jiawei Yu, Xiang Li, Wen Zhang, Jian Luan, Bin Wang, Degen Huang, Jinsong Su
Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research value.
1 code implementation • 26 May 2023 • Kai Zhang, Jun Yu, Eashan Adhikarla, Rong Zhou, Zhiling Yan, Yixin Liu, Zhengliang Liu, Lifang He, Brian Davison, Xiang Li, Hui Ren, Sunyang Fu, James Zou, Wei Liu, Jing Huang, Chen Chen, Yuyin Zhou, Tianming Liu, Xun Chen, Yong Chen, Quanzheng Li, Hongfang Liu, Lichao Sun
Conventional task- and modality-specific artificial intelligence (AI) models are inflexible in real-world deployment and maintenance for biomedicine.
Ranked #1 on Text Summarization on MeQSum
1 code implementation • 23 May 2023 • Qiushi Sun, Nuo Chen, Jianing Wang, Xiang Li, Ming Gao
To tackle the issue, in this paper, we present TransCoder, a unified Transferable fine-tuning strategy for Code representation learning.
1 code implementation • 22 May 2023 • Zheng Li, YuXuan Li, Penghai Zhao, RenJie Song, Xiang Li, Jian Yang
Diffusion models have recently achieved astonishing performance in generating high-fidelity photo-realistic images.
no code implementations • 19 May 2023 • Qiong Chang, Xiang Li, Xin Xu, Xin Liu, Yun Li, Miyazaki Jun
We present a lightweight system for stereo matching through embedded GPUs.
1 code implementation • 19 May 2023 • Fangyu Lei, Xiang Li, Yifan Wei, Shizhu He, Yiming Huang, Jun Zhao, Kang Liu
In this paper, we propose a three-stage TextTableQA framework S3HQA, which comprises of retriever, selector, and reasoner.
no code implementations • 17 May 2023 • Chengcheng Han, Liqing Cui, Renyu Zhu, Jianing Wang, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao
In this paper, we introduce gradient descent into black-box tuning scenario through knowledge distillation.
1 code implementation • 14 May 2023 • Qiushi Sun, Chengcheng Han, Nuo Chen, Renyu Zhu, Jingyang Gong, Xiang Li, Ming Gao
Large language models (LLMs) have shown increasing power on various natural language processing (NLP) tasks.
no code implementations • 13 May 2023 • Chengpei Wu, Yang Lou, Lin Wang, Junli Li, Xiang Li, Guanrong Chen
This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks.
1 code implementation • 10 May 2023 • Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan
We design a dual-intent network to learn user intent from an attention mechanism and the distribution of historical data respectively, which can simulate users' decision-making process in interacting with a new item.
2 code implementations • 9 May 2023 • Xiang Li, Congcong Wen, Yuan Hu, Zhenghang Yuan, Xiao Xiang Zhu
Existing AI-related research in remote sensing primarily focuses on visual understanding tasks while neglecting the semantic understanding of the objects and their relationships.
1 code implementation • 3 May 2023 • Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang
To tackle these limitations, we propose a novel framework that leverages the power of ChatGPT for specific tasks, such as text classification, while improving its interpretability.
no code implementations • 2 May 2023 • Xiang Li, Xin Jiang, Xuying Meng, Aixin Sun, Yequan Wang
FreeLM outperforms large models e. g., GPT-3 and InstructGPT, on a range of language understanding tasks in experiments.
no code implementations • 29 Apr 2023 • Zhenxiang Xiao, Yuzhong Chen, Lu Zhang, Junjie Yao, Zihao Wu, Xiaowei Yu, Yi Pan, Lin Zhao, Chong Ma, Xinyu Liu, Wei Liu, Xiang Li, Yixuan Yuan, Dinggang Shen, Dajiang Zhu, Tianming Liu, Xi Jiang
Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downstream tasks.
no code implementations • 28 Apr 2023 • Jiaqi Wang, Enze Shi, Sigang Yu, Zihao Wu, Chong Ma, Haixing Dai, Qiushi Yang, Yanqing Kang, Jinru Wu, Huawen Hu, Chenxi Yue, Haiyang Zhang, Yiheng Liu, Yi Pan, Zhengliang Liu, Lichao Sun, Xiang Li, Bao Ge, Xi Jiang, Dajiang Zhu, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang
Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on specific tasks.
no code implementations • 25 Apr 2023 • Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang
Additionally, we propose the Debiased LPSA (DLPSA) as a practical application of our jump diffusion approximation result.
no code implementations • 23 Apr 2023 • Wenxiong Liao, Zhengliang Liu, Haixing Dai, Shaochen Xu, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Dajiang Zhu, Hongmin Cai, Tianming Liu, Xiang Li
We focus on analyzing the differences between medical texts written by human experts and generated by ChatGPT, and designing machine learning workflows to effectively detect and differentiate medical texts generated by ChatGPT.
no code implementations • 21 Apr 2023 • Tianyang Zhong, Yaonai Wei, Li Yang, Zihao Wu, Zhengliang Liu, Xiaozheng Wei, Wenjun Li, Junjie Yao, Chong Ma, Xiang Li, Dajiang Zhu, Xi Jiang, Junwei Han, Dinggang Shen, Tianming Liu, Tuo Zhang
The proposed method uses the strengths of LLMs' understanding and logical reasoning to correct the incomplete logical facts for optimizing the performance of perceptual module, by summarizing and reorganizing reasoning rules represented in natural language format.
5 code implementations • 20 Apr 2023 • Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny
Our work, for the first time, uncovers that properly aligning the visual features with an advanced large language model can possess numerous advanced multi-modal abilities demonstrated by GPT-4, such as detailed image description generation and website creation from hand-drawn drafts.
Ranked #9 on Visual Question Answering on BenchLMM
no code implementations • 18 Apr 2023 • Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu
To this end, in this study, we evaluate the performance of ChatGPT/GPT-4 on a radiology NLI task and compare it to other models fine-tuned specifically on task-related data samples.
2 code implementations • 17 Apr 2023 • Chong Ma, Zihao Wu, Jiaqi Wang, Shaochen Xu, Yaonai Wei, Fang Zeng, Zhengliang Liu, Xi Jiang, Lei Guo, Xiaoyan Cai, Shu Zhang, Tuo Zhang, Dajiang Zhu, Dinggang Shen, Tianming Liu, Xiang Li
The 'Impression' section of a radiology report is a critical basis for communication between radiologists and other physicians, and it is typically written by radiologists based on the 'Findings' section.
1 code implementation • 14 Apr 2023 • Yiqun Yao, Siqi Fan, Xiusheng Huang, Xuezhi Fang, Xiang Li, Ziyi Ni, Xin Jiang, Xuying Meng, Peng Han, Shuo Shang, Kang Liu, Aixin Sun, Yequan Wang
With around 14% of the one-time pre-training cost, we can accurately forecast the loss for models up to 52B.
1 code implementation • 9 Apr 2023 • Jun Chen, Deyao Zhu, Kilichbek Haydarov, Xiang Li, Mohamed Elhoseiny
Video captioning aims to convey dynamic scenes from videos using natural language, facilitating the understanding of spatiotemporal information within our environment.
1 code implementation • CVPR 2023 • Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny
Video generation remains a challenging task due to spatiotemporal complexity and the requirement of synthesizing diverse motions with temporal consistency.
no code implementations • 4 Apr 2023 • Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge
This paper presents a comprehensive survey of ChatGPT-related (GPT-3. 5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains.
no code implementations • 1 Apr 2023 • Jason Holmes, Zhengliang Liu, Lian Zhang, Yuzhen Ding, Terence T. Sio, Lisa A. McGee, Jonathan B. Ashman, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu
We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions.
no code implementations • 28 Mar 2023 • Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen, Haixing Dai, Xiaowei Yu, Zhengliang Liu, Tuo Zhang, Xintao Hu, Xi Jiang, Xiang Li, Dajiang Zhu, Dinggang Shen, Tianming Liu
Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do.
1 code implementation • 27 Mar 2023 • Xiang Li, Mingfu Shao
Methods have been proposed to bridge paired-end reads in the presence of reference genome (called reference-based bridging), but the algorithms are far away from scaling for de novo bridging as the underlying compacted de Bruijn graph(cdBG) used in the latter task often contains millions of vertices and edges.
1 code implementation • 23 Mar 2023 • Xiang Li, Ge Wu, Lingfeng Yang, Wenhai Wang, RenJie Song, Jian Yang
The various types of elements, deposited in the training history, are a large amount of wealth for improving learning deep models.
1 code implementation • 20 Mar 2023 • Zhengliang Liu, Yue Huang, Xiaowei Yu, Lu Zhang, Zihao Wu, Chao Cao, Haixing Dai, Lin Zhao, Yiwei Li, Peng Shu, Fang Zeng, Lichao Sun, Wei Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Dajiang Zhu, Xiang Li
The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy.
1 code implementation • ICCV 2023 • YuXuan Li, Qibin Hou, Zhaohui Zheng, Ming-Ming Cheng, Jian Yang, Xiang Li
To the best of our knowledge, this is the first time that large and selective kernel mechanisms have been explored in the field of remote sensing object detection.
Ranked #1 on Semantic Segmentation on UAVid