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cs.CL2026
CTRL-RAG: Contrastive Likelihood Reward Based Reinforcement Learning for Context-Faithful RAG Models
Zhehao Tan, Yihan Jiao, Dan Yang +8
With the growing use of Retrieval-Augmented Generation (RAG), training large language models (LLMs) for context-sensitive reasoning and faithfulness is increasingly important. Exis…
cs.CL2026
Lowest Span Confidence: Zero-Shot Hallucination Detection from a Single LLM Response
Yitong Qiao, Licheng Pan, Yu Mi +6
Hallucinations in Large Language Models (LLMs), i.e., plausible but non-factual generations, pose a significant challenge to reliable deployment in high-stakes environments. Howeve…