no code implementations • EMNLP 2021 • Deyu Zhou, Jianan Wang, Linhai Zhang, Yulan He
Implicit sentiment analysis, aiming at detecting the sentiment of a sentence without sentiment words, has become an attractive research topic in recent years.
no code implementations • 28 Mar 2024 • Rihui Jin, Yu Li, Guilin Qi, Nan Hu, Yuan-Fang Li, Jiaoyan Chen, Jianan Wang, Yongrui Chen, Dehai Min
Table understanding (TU) has achieved promising advancements, but it faces the challenges of the scarcity of manually labeled tables and the presence of complex table structures. To address these challenges, we propose HGT, a framework with a heterogeneous graph (HG)-enhanced large language model (LLM) to tackle few-shot TU tasks. It leverages the LLM by aligning the table semantics with the LLM's parametric knowledge through soft prompts and instruction turning and deals with complex tables by a multi-task pre-training scheme involving three novel multi-granularity self-supervised HG pre-training objectives. We empirically demonstrate the effectiveness of HGT, showing that it outperforms the SOTA for few-shot complex TU on several benchmarks.
no code implementations • 18 Mar 2024 • Bojia Zi, Shihao Zhao, Xianbiao Qi, Jianan Wang, Yukai Shi, Qianyu Chen, Bin Liang, Kam-Fai Wong, Lei Zhang
To this end, this paper proposes a novel text-guided video inpainting model that achieves better consistency, controllability and compatibility.
no code implementations • 16 Mar 2024 • Hongxiang Zhao, Xili Dai, Jianan Wang, Shengbang Tong, Jingyuan Zhang, Weida Wang, Lei Zhang, Yi Ma
This consequently limits the performance of downstream tasks, such as image-to-multiview generation and 3D reconstruction.
no code implementations • 9 Jan 2024 • Junming Chen, Yunfei Liu, Jianan Wang, Ailing Zeng, Yu Li, Qifeng Chen
We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length.
no code implementations • 14 Dec 2023 • Boshi Tang, Jianan Wang, Zhiyong Wu, Lei Zhang
Although Score Distillation Sampling (SDS) has exhibited remarkable performance in conditional 3D content generation, a comprehensive understanding of its formulation is still lacking, hindering the development of 3D generation.
no code implementations • 18 Oct 2023 • Xinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li, Lei Zhang, Jian Zhang, Li Yuan
Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies.
no code implementations • 16 Oct 2023 • Yukai Shi, Jianan Wang, He Cao, Boshi Tang, Xianbiao Qi, Tianyu Yang, Yukun Huang, Shilong Liu, Lei Zhang, Heung-Yeung Shum
In this paper, we present TOSS, which introduces text to the task of novel view synthesis (NVS) from just a single RGB image.
no code implementations • 12 Oct 2023 • Haohan Weng, Tianyu Yang, Jianan Wang, Yu Li, Tong Zhang, C. L. Philip Chen, Lei Zhang
Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability.
no code implementations • 5 Sep 2023 • Bojia Zi, Xianbiao Qi, Lingzhi Wang, Jianan Wang, Kam-Fai Wong, Lei Zhang
In this paper, we present Delta-LoRA, which is a novel parameter-efficient approach to fine-tune large language models (LLMs).
no code implementations • 21 Jun 2023 • Yukun Huang, Jianan Wang, Yukai Shi, Boshi Tang, Xianbiao Qi, Lei Zhang
Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation.
no code implementations • 15 Jun 2023 • Xianbiao Qi, Jianan Wang, Lei Zhang
This article provides a comprehensive understanding of optimization in deep learning, with a primary focus on the challenges of gradient vanishing and gradient exploding, which normally lead to diminished model representational ability and training instability, respectively.
1 code implementation • 12 Jun 2023 • Tianhe Ren, Shilong Liu, Feng Li, Hao Zhang, Ailing Zeng, Jie Yang, Xingyu Liao, Ding Jia, Hongyang Li, He Cao, Jianan Wang, Zhaoyang Zeng, Xianbiao Qi, Yuhui Yuan, Jianwei Yang, Lei Zhang
To address this issue, we develop a unified, highly modular, and lightweight codebase called detrex, which supports a majority of the mainstream DETR-based instance recognition algorithms, covering various fundamental tasks, including object detection, segmentation, and pose estimation.
1 code implementation • 19 Apr 2023 • Xianbiao Qi, Jianan Wang, Yihao Chen, Yukai Shi, Lei Zhang
In contrast to previous practical tricks that address training instability by learning rate warmup, layer normalization, attention formulation, and weight initialization, we show that Lipschitz continuity is a more essential property to ensure training stability.
1 code implementation • CVPR 2023 • Yihao Chen, Xianbiao Qi, Jianan Wang, Lei Zhang
In this way, we can reduce the GPU memory consumption of contrastive loss computation from $\bigO(B^2)$ to $\bigO(\frac{B^2}{N})$, where $B$ and $N$ are the batch size and the number of GPUs used for training.
1 code implementation • ICCV 2023 • Xuan Ju, Ailing Zeng, Chenchen Zhao, Jianan Wang, Lei Zhang, Qiang Xu
While such a plug-and-play approach is appealing, the inevitable and uncertain conflicts between the original images produced from the frozen SD branch and the given condition incur significant challenges for the learnable branch, which essentially conducts image feature editing for condition enforcement.
1 code implementation • CVPR 2023 • Xuan Ju, Ailing Zeng, Jianan Wang, Qiang Xu, Lei Zhang
Humans have long been recorded in a variety of forms since antiquity.
1 code implementation • 22 Feb 2023 • Yikai Wang, Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Wei zhang, Yanwei Fu
In the image manipulation phase, SeMani adopts a generative model to synthesize new images conditioned on the entity-irrelevant regions and target text descriptions.
no code implementations • 1 Jan 2023 • Lu Jiang, Yuanhan Li, Na Luo, Jianan Wang, Qiao Ning
Thirdly, we uses the points of interest(POI) around the rental house information generates a variety of spatial network graphs, and learns the embedding of the network to obtain the spatial feature embedding.
no code implementations • 1 Jan 2023 • Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin
To tackle the challenges, we formulate the problem as a course representation learning task-based and develop an Information-aware Graph Representation Learning(IaGRL) for multi-view MOOC quality evaluation.
no code implementations • 28 Dec 2022 • He Cao, Jianan Wang, Tianhe Ren, Xianbiao Qi, Yihao Chen, Yuan YAO, Lei Zhang
We further provide a hypothesis on the implication of disentangling the generative backbone as an encoder-decoder structure and show proof-of-concept experiments verifying the effectiveness of a stronger encoder for generative tasks with ASymmetriC ENcoder Decoder (ASCEND).
no code implementations • 24 Dec 2022 • Yanan Xiao, Minyu Liu, Zichen Zhang, Lu Jiang, Minghao Yin, Jianan Wang
We propose to formulate the problem as a continuous reinforcement learning task, where the agent is the next flow value predictor, the action is the next time-series flow value in the sensor, and the environment state is a dynamically fused representation of the sensor and transportation network.
1 code implementation • CVPR 2022 • Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Chunjing Xu, Yanwei Fu
Existing text-guided image manipulation methods aim to modify the appearance of the image or to edit a few objects in a virtual or simple scenario, which is far from practical application.
1 code implementation • 15 Nov 2020 • Jianan Wang, Boyang Li, Xiangyu Fan, Jing Lin, Yanwei Fu
The task of video and text sequence alignment is a prerequisite step toward joint understanding of movie videos and screenplays.
1 code implementation • NeurIPS 2020 • Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
Our main postulate is that the combination of task segmentation, modular learning and memory-based ensembling can give rise to generalization on an exponentially growing number of unseen tasks.
no code implementations • NeurIPS 2020 • Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
We introduce a new and completely online contextual bandit algorithm called Gated Linear Contextual Bandits (GLCB).
2 code implementations • 30 Sep 2019 • Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter
This paper presents a new family of backpropagation-free neural architectures, Gated Linear Networks (GLNs).
1 code implementation • NeurIPS 2019 • Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang, Andrew Markham, Niki Trigoni
The framework directly regresses 3D bounding boxes for all instances in a point cloud, while simultaneously predicting a point-level mask for each instance.
Ranked #13 on 3D Instance Segmentation on S3DIS (mPrec metric)
no code implementations • 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS) 2019 • Peijun Zhao, Chris Xiaoxuan Lu, Jianan Wang, Changhao Chen, Wei Wang, Niki Trigoni, and Andrew Markham
The key to offering personalised services in smart spaces is knowing where a particular person is with a high degree of accuracy.
no code implementations • WS 2017 • Jianan Wang, Xin Wang, Fang Li, Zhen Xu, Zhuoran Wang, Baoxun Wang
For practical chatbots, one of the essential factor for improving user experience is the capability of customizing the talking style of the agents, that is, to make chatbots provide responses meeting users{'} preference on language styles, topics, etc.
no code implementations • IJCNLP 2017 • Xin Wang, Jianan Wang, Yuanchao Liu, Xiaolong Wang, Zhuoran Wang, Baoxun Wang
Besides, strategies of obtaining distance supervision data for pre-training are also discussed in this work.