5 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…
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…
Memorization Understanding: Do Large Language Models Have the Ability of Scenario Cognition?
Boxiang Ma, Ru Li, Yuanlong Wang +2
Driven by vast and diverse textual data, large language models (LLMs) have demonstrated impressive performance across numerous natural language processing (NLP) tasks. Yet, a criti…
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…