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cs.CL2026
In-Situ Behavioral Evaluation for LLM Fairness, Not Standardized-Test Scores
Zeyu Tang, Sang T. Truong, Deonna Owens +4
LLM fairness should be evaluated through in-situ behavioral pattern rather than standardized-test Q&A benchmarks. We show that the standardized-test paradigm can be structurally un…
cs.CL2025
Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs
Aryan Gulati, Brando Miranda, Eric Chen +5
Current mathematical reasoning benchmarks for large language models (LLMs) are approaching saturation, with some achieving > 90% accuracy, and are increasingly compromised by train…