23 citations · 24 across the 7 of their papers we have counts for
6 papers · 1 filter
CARD: Towards Conditional Design of Multi-agent Topological Structures
Tongtong Wu, Yanming Li, Ziye Tang +5
Large language model (LLM)-based multi-agent systems have shown strong capabilities in tasks such as code generation and collaborative reasoning. However, the effectiveness and rob…
Beyond Memorization: A Rigorous Evaluation Framework for Medical Knowledge Editing
Shigeng Chen, Linhao Luo, Zhangchi Qiu +3
Recently, knowledge editing (KE) has emerged as a promising approach to update specific facts in Large Language Models (LLMs) without the need for full retraining. Despite the effe…
Graph Retrieval-Augmented LLM for Conversational Recommendation Systems
Zhangchi Qiu, Linhao Luo, Zicheng Zhao +2
Conversational Recommender Systems (CRSs) have emerged as a transformative paradigm for offering personalized recommendations through natural language dialogue. However, they face…
Reasoning over User Preferences: Knowledge Graph-Augmented LLMs for Explainable Conversational Recommendations
Zhangchi Qiu, Linhao Luo, Shirui Pan +1
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by capturing user preferences through interactive dialogues. Explainability in CRSs is crucial…
Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models
Linhao Luo, Zicheng Zhao, Gholamreza Haffari +3
Large language models (LLMs) have demonstrated impressive reasoning abilities, but they still struggle with faithful reasoning due to knowledge gaps and hallucinations. To address…
Continual Learning for Large Language Models: A Survey
Tongtong Wu, Linhao Luo, Yuan-Fang Li +3
Large language models (LLMs) are not amenable to frequent re-training, due to high training costs arising from their massive scale. However, updates are necessary to endow LLMs wit…