3 citations · 7 across the 16 of their papers we have counts for
9 papers · 1 filter
PathMind: A Retrieve-Prioritize-Reason Framework for Knowledge Graph Reasoning with Large Language Models
Yu Liu, Xixun Lin, Yanmin Shang +3
Knowledge graph reasoning (KGR) is the task of inferring new knowledge by performing logical deductions on knowledge graphs. Recently, large language models (LLMs) have demonstrate…
V-ITI: Mitigating Hallucinations in Multimodal Large Language Models via Visual Inference-Time Intervention
Nan Sun, Zhenyu Zhang, Xixun Lin +8
Multimodal Large Language Models (MLLMs) excel in numerous vision-language tasks yet suffer from hallucinations, producing content inconsistent with input visuals, that undermine r…
MAD-Fact: A Multi-Agent Debate Framework for Long-Form Factuality Evaluation in LLMs
Yucheng Ning, Xixun Lin, Fang Fang +1
The widespread adoption of Large Language Models (LLMs) raises critical concerns about the factual accuracy of their outputs, especially in high-risk domains such as biomedicine, l…
LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions
Xixun Lin, Yucheng Ning, Jingwen Zhang +21
Driven by the rapid advancements of Large Language Models (LLMs), LLM-based agents have emerged as powerful intelligent systems capable of human-like cognition, reasoning, and inte…
Enhancing Large Language Model for Knowledge Graph Completion via Structure-Aware Alignment-Tuning
Yu Liu, Yanan Cao, Xixun Lin +3
Knowledge graph completion (KGC) aims to infer new knowledge and make predictions from knowledge graphs. Recently, large language models (LLMs) have exhibited remarkable reasoning…
RANA: Robust Active Learning for Noisy Network Alignment
Yixuan Nan, Xixun Lin, Yanmin Shang +3
Network alignment has attracted widespread attention in various fields. However, most existing works mainly focus on the problem of label sparsity, while overlooking the issue of n…
Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs
Nan Sun, Xixun Lin, Zhiheng Zhou +3
Recently, Out-of-distribution (OOD) detection in dynamic graphs, which aims to identify whether incoming data deviates from the distribution of the in-distribution (ID) training se…
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…
Large Language Models for Planning: A Comprehensive and Systematic Survey
Pengfei Cao, Tianyi Men, Wencan Liu +7
Planning represents a fundamental capability of intelligent agents, requiring comprehensive environmental understanding, rigorous logical reasoning, and effective sequential decisi…