Papers with Search-AuGmented Evaluation

1 papers
SAGE: A Search-AuGmented Evaluation of Large Language Models on Free-Form QA (2026.acl-long)

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Challenge: Large Language Models (LLMs) are prone to hallucination and rely on static, pre-annotated references for evaluation.
Approach: They propose a framework to assess large language models without fixed ground-truth answers by iteratively generating web queries and synthesizing external evidence.
Outcome: The proposed framework achieves substantial to perfect agreement with human evaluations on multiple free-form QA benchmarks.

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