44 citations · 82 across the 17 of their papers we have counts for
17 papers
Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
Xiaodong Li, Jiawei Sheng, Jiangxia Cao +6
Cross-domain recommendation (CDR) has demonstrated to be an effective solution for alleviating the user cold-start issue. By leveraging rich user-item interactions available in a r…
S2CDR: Smoothing-Sharpening Process Model for Cross-Domain Recommendation
Xiaodong Li, Juwei Yue, Xinghua Zhang +5
User cold-start problem is a long-standing challenge in recommendation systems. Fortunately, cross-domain recommendation (CDR) has emerged as a highly effective remedy for the user…
ATTNPO: Attention-Guided Process Supervision for Efficient Reasoning
Shuaiyi Nie, Siyu Ding, Wenyuan Zhang +7
Large reasoning models trained with reinforcement learning and verifiable rewards (RLVR) achieve strong performance on complex reasoning tasks, yet often overthink, generating redu…
ExpSeek: Self-Triggered Experience Seeking for Web Agents
Wenyuan Zhang, Xinghua Zhang, Haiyang Yu +5
Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insights from accumulated experience…
Exploring the System 1 Thinking Capability of Large Reasoning Models
Wenyuan Zhang, Shuaiyi Nie, Xinghua Zhang +2
This paper explores the system 1 thinking capability of Large Reasoning Models (LRMs), the intuitive ability to respond efficiently with minimal token usage. While existing LRMs re…
SOTOPIA-: Dynamic Strategy Injection Learning and Social Instruction Following Evaluation for Social Agents
Wenyuan Zhang, Tianyun Liu, Mengxiao Song +2
Despite the abundance of prior social strategies possessed by humans, there remains a paucity of research dedicated to their transfer and integration into social agents. Our propos…
MoR: Mixture of Ranks for Low-Rank Adaptation Tuning
Chuanyu Tang, Yilong Chen, Zhenyu Zhang +4
Low-Rank Adaptation (LoRA) drives research to align its performance with full fine-tuning. However, significant challenges remain: (1) Simply increasing the rank size of LoRA does…
Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing
Wenyuan Zhang, Shuaiyi Nie, Jiawei Sheng +4
Large language model (LLM) role-playing has gained widespread attention. Authentic character knowledge is crucial for constructing realistic LLM role-playing agents. However, exist…
Optimal Transport Guided Correlation Assignment for Multimodal Entity Linking
Zefeng Zhang, Jiawei Sheng, Chuang Zhang +4
Multimodal Entity Linking (MEL) aims to link ambiguous mentions in multimodal contexts to entities in a multimodal knowledge graph. A pivotal challenge is to fully leverage multi-e…
Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning
Yongquan He, Wenyuan Zhang, Xuancheng Huang +5
Instruction tuning for large language models (LLMs) can drive them to produce results consistent with human goals in specific downstream tasks. However, the process of continual in…
HIP Network: Historical Information Passing Network for Extrapolation Reasoning on Temporal Knowledge Graph
Yongquan He, Peng Zhang, Luchen Liu +3
In recent years, temporal knowledge graph (TKG) reasoning has received significant attention. Most existing methods assume that all timestamps and corresponding graphs are availabl…
Adaptive Data Augmentation for Aspect Sentiment Quad Prediction
Wenyuan Zhang, Xinghua Zhang, Shiyao Cui +3
Aspect sentiment quad prediction (ASQP) aims to predict the quad sentiment elements for a given sentence, which is a critical task in the field of aspect-based sentiment analysis.…
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
Xiaodong Li, Jiawei Sheng, Jiangxia Cao +3
Cross-domain recommendation (CDR) has been proven as a promising way to tackle the user cold-start problem, which aims to make recommendations for users in the target domain by tra…
FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, Toxicity
Shiyao Cui, Zhenyu Zhang, Yilong Chen +4
The widespread of generative artificial intelligence has heightened concerns about the potential harms posed by AI-generated texts, primarily stemming from factoid, unfair, and tox…
A Boundary Offset Prediction Network for Named Entity Recognition
Minghao Tang, Yongquan He, Yongxiu Xu +3
Named entity recognition (NER) is a fundamental task in natural language processing that aims to identify and classify named entities in text. However, span-based methods for NER t…
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning
Minghao Tang, Yongquan He, Yongxiu Xu +3
Fine-grained entity typing (FET) is an essential task in natural language processing that aims to assign semantic types to entities in text. However, FET poses a major challenge kn…
Dynamic Multi-Scale Context Aggregation for Conversational Aspect-Based Sentiment Quadruple Analysis
Yuqing Li, Wenyuan Zhang, Binbin Li +3
Conversational aspect-based sentiment quadruple analysis (DiaASQ) aims to extract the quadruple of target-aspect-opinion-sentiment within a dialogue. In DiaASQ, a quadruple's eleme…