Domain-Specific Hallucination Detection in Large Language Models
A multi-signal pipeline detects LLM hallucinations, reaching F1 0.915 on HaluEval and cutting Qwen2.5-0.5B hallucination rates from 85.5% to 37.7% via DPO.
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Stories tagged #hallucination-detection
CodeTD: Topology of Attention Detects Hallucinations in Code LLMs
CodeTD detects hallucinations in code LLMs before execution by analyzing topological patterns of attention maps, outperforming recent baselines.
Enoki: Efficient Multi-Level Hallucination Detection
Researchers introduce Enoki, an open information extraction framework unifying claim-level and span-level hallucination detection in LLMs at lower inference cost.