[UAI 2026 Oral] SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory, which aims to detect hallucinated content in LLM-generated text.
python nlp black-box information-theory pytorch question-answering uncertainty-quantification trustworthy-ai llm hallucination-detection llm-hallucination semantic-entropy llm-uncertainty structural-entropy uai-2026
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Updated
Jul 6, 2026 - Python