From Tokens to Semantics: Leveraging Complementary Signals for Hallucination Detection in Black-Box LLMs
Paper recorded by Signals 4 on 2026-09-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-02 on arXiv · recorded by Signals 4 on 2026-09-03
Category: cs.AI · 人工智能 · first seen 2026-09-03
Abstract
When LLMs support public-facing or high-stakes workflows, missed fabrications can harm users and institutions, while false alarms consume limited human-review capacity. When no trusted context or reference document is available, we study two signals accessible through black-box model APIs: semantic entropy, which measures disagreement among sampled response meanings, and uncertainty derived from t
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Cite this page: From Tokens to Semantics: Leveraging Complementary Signals for Hallucination Detection in Black-Box LLMs: the #219 most recent of 300 cs.AI papers we have recorded (as of 2026-09-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/from-tokens-to-semantics-leveraging-complementary-signals-for-hallucination-dete.html
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