7 papers
CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering
Zhichao Yan, Shizhao Li, Jiapu Wang +5
Long-form question answering increasingly relies on retrieved evidence to make LLM outputs verifiable, with inline citations tracing claims to source documents. However, existing s…
Beyond Factual Accuracy: Evaluating Global Reasoning Integrity in RAG Systems with LogicScore
Zhichao Yan, Yunxiao Zhao, Jiapu Wang +4
Current evaluation methods for Retrieval Augmented Generation (RAG) suffer from \textit{factual myopia}: they relentlessly emphasize factual accuracy yet neglect global logical int…
Cumulative Path-Level Semantic Reasoning for Inductive Knowledge Graph Completion
Jiapu Wang, Xinghe Cheng, Zezheng Wu +6
Conventional Knowledge Graph Completion (KGC) methods aim to infer missing information in incomplete Knowledge Graphs (KGs) by leveraging existing information, which struggle to pe…
A Large-Scale Chinese Knowledge Graph-Text Alignment Dataset for Benchmarking Knowledge-Grounded LLMs
Chengwei Wu, Jiapu Wang, Mingyang Gao +10
Reliable evaluation of knowledge-grounded Large Language Models (LLMs) in Chinese requires resources that explicitly align Chinese-language text with verifiable Knowledge Graph (KG…
Atomic Fact Decomposition Helps Attributed Question Answering
Zhichao Yan, Jiapu Wang, Jiaoyan Chen +3
Attributed Question Answering (AQA) aims to provide both a trustworthy answer and a reliable attribution report for a given question. Retrieval is a widely adopted approach, includ…
Prompting Large Language Models with Partial Knowledge for Answering Questions with Unseen Entities
Zhichao Yan, Jiapu Wang, Jiaoyan Chen +6
Retrieval-Augmented Generation (RAG) shows impressive performance by supplementing and substituting parametric knowledge in Large Language Models (LLMs). Retrieved knowledge can be…