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cs.LG2026
DualEval: Joint Model-Item Calibration for Unified LLM Evaluation
Aaron J. Li, Hao Huang, Youngmin Park +6
Current LLM evaluation relies on two complementary but often disconnected signals: static benchmarks with objective correctness labels and arena-style preference data that better r…
cs.LG2025
Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders
Aaron J. Li, Suraj Srinivas, Usha Bhalla +1
Sparse autoencoders (SAEs) are commonly used to interpret the internal activations of large language models (LLMs) by mapping them to human-interpretable concept representations. W…