no code implementations • Findings (NAACL) 2022 • Le Qi, Yu Zhang, Qingyu Yin, Guidong Zheng, Wen Junjie, Jinlong Li, Ting Liu
In this process, there are two kinds of critical information that are commonly employed: the representation information of original questions and the interactive information between pairs of questions.
no code implementations • 27 Mar 2024 • Xiusi Chen, Hongzhi Wen, Sreyashi Nag, Chen Luo, Qingyu Yin, Ruirui Li, Zheng Li, Wei Wang
Such a constitution discovery pipeline can be run iteratively and automatically to discover new constitutions that specifically target the alignment gaps in the current LLM.
1 code implementation • 15 Mar 2024 • Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration.
no code implementations • 7 Feb 2024 • Qingyu Yin, Xuzheng He, Xiang Zhuang, Yu Zhao, Jianhua Yao, Xiaoyu Shen, Qiang Zhang
The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling.
1 code implementation • 26 Jan 2024 • Qiang Zhang, Keyang Ding, Tianwen Lyv, Xinda Wang, Qingyu Yin, Yiwen Zhang, Jing Yu, Yuhao Wang, Xiaotong Li, Zhuoyi Xiang, Xiang Zhuang, Zeyuan Wang, Ming Qin, Mengyao Zhang, Jinlu Zhang, Jiyu Cui, Renjun Xu, Hongyang Chen, Xiaohui Fan, Huabin Xing, Huajun Chen
Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence.
no code implementations • 21 Dec 2023 • Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song
In this paper, we introduce the task of logical session complex query answering, where sessions are treated as hyperedges of items, and we formulate the problem of complex intention understanding as a task of logical session complex queries answering (LS-CQA) on an aggregated hypergraph of sessions, items, and attributes.
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.
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 • 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.
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.
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.
1 code implementation • EMNLP 2021 • Qi Shi, Yu Zhang, Qingyu Yin, Ting Liu
Specifically, we first retrieve logic-level program-like evidence from the given table and statement as supplementary evidence for the table.
no code implementations • 29 Dec 2020 • Le Qi, Yu Zhang, Qingyu Yin, Ting Liu
Self attention networks (SANs) have been widely utilized in recent NLP studies.
no code implementations • COLING 2020 • Qi Shi, Yu Zhang, Qingyu Yin, Ting Liu
Table-based fact verification is expected to perform both linguistic reasoning and symbolic reasoning.
1 code implementation • 25 Nov 2020 • Jie Ma, Qi Chai, Jun Liu, Qingyu Yin, Pinghui Wang, Qinghua Zheng
Textbook Question Answering (TQA) is a task that one should answer a diagram/non-diagram question given a large multi-modal context consisting of abundant essays and diagrams.
no code implementations • 13 Feb 2020 • Funan Mu, Zhenting Yu, LiFeng Wang, Yequan Wang, Qingyu Yin, Yibo Sun, Liqun Liu, Teng Ma, Jing Tang, Xing Zhou
In addition, with the help of tokens, our model is able to extract overlapped keyphrases.
no code implementations • ACL 2019 • Hui Liu, Qingyu Yin, William Yang Wang
Building explainable systems is a critical problem in the field of Natural Language Processing (NLP), since most machine learning models provide no explanations for the predictions.
1 code implementation • COLING 2018 • Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu, William Yang Wang
Recent neural network methods for zero pronoun resolution explore multiple models for generating representation vectors for zero pronouns and their candidate antecedents.
1 code implementation • ACL 2018 • Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu, William Yang Wang
In this study, we show how to integrate local and global decision-making by exploiting deep reinforcement learning models.
no code implementations • EMNLP 2017 • Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu
Existing approaches for Chinese zero pronoun resolution typically utilize only syntactical and lexical features while ignoring semantic information.
no code implementations • ACL 2017 • Ting Liu, Yiming Cui, Qingyu Yin, Wei-Nan Zhang, Shijin Wang, Guoping Hu
Most existing approaches for zero pronoun resolution are heavily relying on annotated data, which is often released by shared task organizers.
no code implementations • 7 May 2016 • Wei-Nan Zhang, Ting Liu, Qingyu Yin, Yu Zhang
Dropped pronouns (DPs) are ubiquitous in pro-drop languages like Chinese, Japanese etc.
no code implementations • 20 Apr 2016 • Qingyu Yin, Wei-Nan Zhang, Yu Zhang, Ting Liu
This is because zero pronouns have no descriptive information, which results in difficulty in explicitly capturing their semantic similarities with antecedents.