Search Results for author: Qingyu Yin

Found 28 papers, 8 papers with code

All Information is Valuable: Question Matching over Full Information Transmission Network

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.

IterAlign: Iterative Constitutional Alignment of Large Language Models

no code implementations27 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.

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

no code implementations15 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.

Explanation Generation Image Generation

StableMask: Refining Causal Masking in Decoder-only Transformer

no code implementations7 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.

Language Modelling Position

Scientific Large Language Models: A Survey on Biological & Chemical Domains

1 code implementation26 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.

Understanding Inter-Session Intentions via Complex Logical Reasoning

no code implementations21 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.

Attribute Complex Query Answering +1

Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels

no code implementations5 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.

Image Captioning Text Generation

Knowledge Graph Reasoning over Entities and Numerical Values

1 code implementation2 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.

Attribute Complex Query Answering

Graph Reasoning for Question Answering with Triplet Retrieval

no code implementations30 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.

Knowledge Graphs Question Answering +1

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites

no code implementations15 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.

Graph Attention

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks

no code implementations15 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.

Node Classification

RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

no code implementations12 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.

Product Recommendation Retrieval

Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification

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.

Fact Verification Retrieval +1

XTQA: Span-Level Explanations of the Textbook Question Answering

1 code implementation25 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.

Question Answering

Towards Explainable NLP: A Generative Explanation Framework for Text Classification

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.

BIG-bench Machine Learning General Classification +2

Zero Pronoun Resolution with Attention-based Neural Network

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.

Chinese Zero Pronoun Resolution

Chinese Zero Pronoun Resolution with Deep Memory Network

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.

Chinese Zero Pronoun Resolution Descriptive +2

Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution

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.

Reading Comprehension

Neural Recovery Machine for Chinese Dropped Pronoun

no code implementations7 May 2016 Wei-Nan Zhang, Ting Liu, Qingyu Yin, Yu Zhang

Dropped pronouns (DPs) are ubiquitous in pro-drop languages like Chinese, Japanese etc.

Feature Engineering

A Deep Neural Network for Chinese Zero Pronoun Resolution

no code implementations20 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.

Chinese Zero Pronoun Resolution Descriptive

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