no code implementations • EMNLP 2021 • Zheng Li, Danqing Zhang, Tianyu Cao, Ying WEI, Yiwei Song, Bing Yin
In this work, we explore multilingual sequence labeling with minimal supervision using a single unified model for multiple languages.
no code implementations • EMNLP 2020 • Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying WEI, Yu Zhang, Qiang Yang
Recent emergence of multilingual pre-training language model (mPLM) has enabled breakthroughs on various downstream cross-lingual transfer (CLT) tasks.
no code implementations • 6 Feb 2024 • Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang
OPPU integrates parametric user knowledge in the personal PEFT parameters with the non-parametric knowledge acquired through retrieval and profile.
1 code implementation • NeurIPS 2023 • Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song
The goal of session-based recommendation in E-commerce is to predict the next item that an anonymous user will purchase based on the browsing and purchase history.
no code implementations • 1 Nov 2023 • Shi Yin, Shijie Huan, Shangfei Wang, Jinshui Hu, Tao Guo, Bing Yin, BaoCai Yin, Cong Liu
For temporal modeling, we propose a recurrent token mixing mechanism, an axis-landmark-positional embedding mechanism, as well as a confidence-enhanced multi-head attention mechanism to adaptively and robustly embed long-term landmark dynamics into their 1D representations; for structure modeling, we design intra-group and inter-group structure modeling mechanisms to encode the component-level as well as global-level facial structure patterns as a refinement for the 1D representations of landmarks through token communications in the spatial dimension via 1D convolutional layers.
no code implementations • 27 Aug 2023 • Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, Bing Yin
Situated NLE provides a perspective and facilitates further research on the generation and evaluation of explanations.
no code implementations • 4 Aug 2023 • Yin Lin, Cong Liu, Yehansen Chen, Jinshui Hu, Bing Yin, BaoCai Yin, Zengfu Wang
Recently, visual-language learning has shown great potential in enhancing visual-based person re-identification (ReID).
1 code implementation • NeurIPS 2023 • Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
To test the potential of the dataset, we introduce three tasks in this work: (1) next-product recommendation, (2) next-product recommendation with domain shifts, and (3) next-product title generation.
no code implementations • 5 Jul 2023 • Bang Yang, Fenglin Liu, Zheng Li, Qingyu Yin, Chenyu You, Bing Yin, Yuexian Zou
We observe that the core challenges of novel product title generation are the understanding of novel product characteristics and the generation of titles in a novel writing style.
no code implementations • 25 Jun 2023 • Yangchen Xie, Xinyuan Chen, Hongjian Zhan, Palaiahankote Shivakum, Bing Yin, Cong Liu, Yue Lu
A large number of annotated training images is crucial for training successful scene text recognition models.
no code implementations • 14 Jun 2023 • Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang
Therefore, in this work, we study a novel problem of developing robust and membership privacy-preserving GNNs.
1 code implementation • 2 Jun 2023 • Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song
To address the difference between entities and numerical values, we also propose the framework of Number Reasoning Network (NRN) for alternatively encoding entities and numerical values into separate encoding structures.
no code implementations • 30 May 2023 • Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin
State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e. g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering.
no code implementations • 19 May 2023 • Jie Huang, Yifan Gao, Zheng Li, Jingfeng Yang, Yangqiu Song, Chao Zhang, Zining Zhu, Haoming Jiang, Kevin Chen-Chuan Chang, Bing Yin
We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e. g., "Digital Cameras", generating a list of complementary concepts, e. g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers.
1 code implementation • 3 May 2023 • Peifeng Wang, Zhengyang Wang, Zheng Li, Yifan Gao, Bing Yin, Xiang Ren
While CoT can yield dramatically improved performance, such gains are only observed for sufficiently large LMs.
1 code implementation • 26 Apr 2023 • Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu
This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (NLP) tasks.
no code implementations • 3 Apr 2023 • WenBo Hu, Hongjian Zhan, Xinchen Ma, Cong Liu, Bing Yin, Yue Lu
In the field of historical manuscript research, scholars frequently encounter novel symbols in ancient texts, investing considerable effort in their identification and documentation.
no code implementations • 27 Mar 2023 • Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek Abdelzaher
This paper investigates cross-lingual temporal knowledge graph reasoning problem, which aims to facilitate reasoning on Temporal Knowledge Graphs (TKGs) in low-resource languages by transfering knowledge from TKGs in high-resource ones.
1 code implementation • 8 Mar 2023 • Zhenrong Zhang, Pengfei Hu, Jiefeng Ma, Jun Du, Jianshu Zhang, Huihui Zhu, BaoCai Yin, Bing Yin, Cong Liu
Table structure recognition is an indispensable element for enabling machines to comprehend tables.
no code implementations • ICCV 2023 • Shan He, Haonan He, Shuo Yang, Xiaoyan Wu, Pengcheng Xia, Bing Yin, Cong Liu, LiRong Dai, Chang Xu
Besides, we also verify that the proposed framework is able to explicitly control the emotion of the animated talking face.
1 code implementation • 15 Nov 2022 • Changlong Yu, Weiqi Wang, Xin Liu, Jiaxin Bai, Yangqiu Song, Zheng Li, Yifan Gao, Tianyu Cao, Bing Yin
Understanding users' intentions in e-commerce platforms requires commonsense knowledge.
no code implementations • 16 Oct 2022 • Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher
Second, the potentially dynamic distributions from the initially observable facts to the future facts ask for explicitly modeling the evolving characteristics of new entities.
no code implementations • 8 Oct 2022 • Haoming Jiang, Tianyu Cao, Zheng Li, Chen Luo, Xianfeng Tang, Qingyu Yin, Danqing Zhang, Rahul Goutam, Bing Yin
When applying masking to short search queries, most contextual information is lost and the intent of the search queries may be changed.
no code implementations • 15 Sep 2022 • Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao
Specifically, we train a generator to recover identities of the masked edges, and simultaneously, we train a discriminator to distinguish the generated edges from the original graph's edges.
no code implementations • 15 Sep 2022 • Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao
The model subsequently calculates session representations by combining the contextual information with the instant search query using an aggregation network.
no code implementations • 21 Jul 2022 • Dajian Zhong, Shujing Lyu, Palaiahnakote Shivakumara, Bing Yin, Jiajia Wu, Umapada Pal, Yue Lu
For target images (scene text images), the Semantic Generator Module generates simple semantic features that share the same feature distribution with support images (clear text images).
3 code implementations • 15 Jun 2022 • Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin
However, existing approaches have their inherent limitations: (1) they are not directly applicable to graphs where the data is discrete; and (2) the condensation process is computationally expensive due to the involved nested optimization.
1 code implementation • Findings (NAACL) 2022 • Yifan Gao, Qingyu Yin, Zheng Li, Rui Meng, Tong Zhao, Bing Yin, Irwin King, Michael R. Lyu
Keyphrase generation is the task of automatically predicting keyphrases given a piece of long text.
1 code implementation • Findings (NAACL) 2022 • Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang
SeqZero achieves SOTA performance of BART-based models on GeoQuery and EcommerceQuery, which are two few-shot datasets with compositional data split.
no code implementations • NAACL 2022 • Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
User sessions empower many search and recommendation tasks on a daily basis.
1 code implementation • ACL 2022 • Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang
In this paper, we explore multilingual KG completion, which leverages limited seed alignment as a bridge, to embrace the collective knowledge from multiple languages.
Ranked #3 on Knowledge Graph Completion on DPB-5L (French)
no code implementations • 12 Feb 2022 • Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin, Tarek Abdelzaher
And meanwhile, RETE autoregressively accumulates retrieval-enhanced user representations from each time step, to capture evolutionary patterns for joint query and product prediction.
no code implementations • 19 Aug 2021 • Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang
We study the problem of query attribute value extraction, which aims to identify named entities from user queries as diverse surface form attribute values and afterward transform them into formally canonical forms.
1 code implementation • ACL 2021 • Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao
Unfortunately, we observe that weakly labeled data does not necessarily improve, or even deteriorate the model performance (due to the extensive noise in the weak labels) when we train deep NER models over a simple or weighted combination of the strongly labeled and weakly labeled data.
no code implementations • NAACL 2021 • Hanqing Lu, Youna Hu, Tong Zhao, Tony Wu, Yiwei Song, Bing Yin
Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios.
1 code implementation • NAACL 2021 • Hui Liu, Danqing Zhang, Bing Yin, Xiaodan Zhu
In this paper, we explore to improve pretrained models with label hierarchies on the ZS-MTC task.
no code implementations • 22 Sep 2020 • Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin
Our contributions are two-factored: (1) we introduce a new state-of-the-art classifier that uses label attention with RoBERTa and combine it with our augmentation framework for further improvement; (2) we present a broad study on how effective are different augmentation methods in the XMC task.
no code implementations • 20 Dec 2019 • Mukul Kumar, Youna Hu, Will Headden, Rahul Goutam, Heran Lin, Bing Yin
Recent works such as BERT have demonstrated the success of a large transformer encoder architecture with language model pre-training on a variety of NLP tasks.
1 code implementation • 1 Jul 2019 • Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian, Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin
To address these issues, we train a deep learning model for semantic matching using customer behavior data.