HART: Data-Driven Hallucination Attribution and Evidence-Based Tracing for Large Language Models
HART: Data-Driven Hallucination Attribution and Evidence-Based Tracing for Large Language Models explores HART is a framework for fine-grained hallucination attribution and evidence retrieval in LLMs, providing a structured approach to identify and trace the causes of hallucinations.. Commercial viability score: 7/10 in LLM Evaluation.
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