AI RESEARCH
Building Reliable Long-Form Generation via Hallucination Rejection Sampling
arXiv CS.LG
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ArXi:2606.03628v1 Announce Type: cross Large language models (LLMs) have achieved remarkable progress in open-ended text generation, yet they remain prone to hallucinating incorrect or uned content, which undermines their reliability. This issue is exacerbated in long-form generation due to hallucination snowballing, a phenomenon where early errors propagate and compound into subsequent outputs.