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Research questionHow should a single anchor be chosen to produce reliable rankings in LLM evaluation?Single-anchor comparisons reduce the cost of evaluating many models, but the resulting rankings can change substantially with the anchor. Extreme-performing anchors may provide little information about differences among competitive models.
AI
Evaluation & Benchmarks
Natural Language Processing
Latest papersRecent research connected to this question, newest first.Mediocrity is the key for LLM as a Judge Anchor SelectionThe evidence comes from evaluating 22 anchors on the Arena-Hard-v2.0 dataset. It reports reduced agreement with human rankings for poor anchors, poor performance from best- and worst-performing anchors, and benchmark sizes that may not reliably distinguish competitive models.research paper · Sep 2, 2026
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