AutoVerifier decomposes technical claims into triples and uses layered LLM verification to assess validity, demonstrated on a quantum computing paper by finding overclaims and conflicts.
Siren’s song in the ai ocean: A survey on hallucination in large language models.Computational Linguistics, pages 1–46
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ARS shapes reasoning trace representations by clustering states that produce consistent answers and separating those that produce inconsistent ones via latent perturbations, improving plug-and-play hallucination detection without human annotations.
citing papers explorer
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AutoVerifier: An Agentic Automated Verification Framework Using Large Language Models
AutoVerifier decomposes technical claims into triples and uses layered LLM verification to assess validity, demonstrated on a quantum computing paper by finding overclaims and conflicts.
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Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping
ARS shapes reasoning trace representations by clustering states that produce consistent answers and separating those that produce inconsistent ones via latent perturbations, improving plug-and-play hallucination detection without human annotations.