2 citations · 2 across the 11 of their papers we have counts for
4 papers · 1 filter
Semantic Energy: Detecting LLM Hallucination Beyond Entropy
Huan Ma, Jiadong Pan, Jing Liu +7
Large Language Models (LLMs) are being increasingly deployed in real-world applications, but they remain susceptible to hallucinations, which produce fluent yet incorrect responses…
BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation
Yuhao Wang, Ruiyang Ren, Yucheng Wang +4
With the rapid advancement of large language models (LLMs), retrieval-augmented generation (RAG) has emerged as a critical approach to supplement the inherent knowledge limitations…
Unveiling Knowledge Utilization Mechanisms in LLM-based Retrieval-Augmented Generation
Yuhao Wang, Ruiyang Ren, Yucheng Wang +4
Considering the inherent limitations of parametric knowledge in large language models (LLMs), retrieval-augmented generation (RAG) is widely employed to expand their knowledge scop…
Reinforced Informativeness Optimization for Long-Form Retrieval-Augmented Generation
Yuhao Wang, Ruiyang Ren, Yucheng Wang +4
Long-form question answering (LFQA) requires open-ended long-form responses that synthesize coherent, factually grounded content from multi-source evidence. This makes reinforcemen…