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cs.CL2026
RAC: Retrieval-Augmented Clarification for Faithful Conversational Search
Ahmed Rayane Kebir, Vincent Guigue, Lynda Said Lhadj +1
Clarification questions help conversational search systems resolve ambiguous or underspecified user queries. While prior work has focused on fluency and alignment with user intent,…
cs.CL2025
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen +4
Large Language Models (LLMs), when used for conditional text generation, often produce hallucinations, i.e., information that is unfaithful or not grounded in the input context. Th…