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cs.CL2026
FineDialFact: A benchmark for Fine-grained Dialogue Fact Verification
Xiangyan Chen, Yufeng Li, Yujian Gan +2
Large language models are known to produce hallucinations - factually incorrect or fabricated information - which poses significant challenges for many natural language processing…
cs.CL2026
Fine-Refine: Iterative Fine-grained Refinement for Mitigating Dialogue Hallucination
Xiangyan Chen, Yujian Gan, Matthew Purver
The tendency for hallucination in current large language models (LLMs) negatively impacts dialogue systems. Such hallucinations produce factually incorrect responses that may misle…
cs.CL2025
Improving Factuality for Dialogue Response Generation via Graph-Based Knowledge Augmentation
Xiangyan Chen, Yujian Gan, Yimeng Gu +1
Large Language Models (LLMs) succeed in many natural language processing tasks. However, their tendency to hallucinate - generate plausible but inconsistent or factually incorrect…