2 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
Landon Butler, Abhineet Agarwal, Justin Singh Kang +3
Large Language Models (LLMs) have achieved remarkable performance by capturing complex interactions between input features. To identify these interactions, most existing approaches…
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin Singh Kang, Landon Butler, Abhineet Agarwal +4
Large language models (LLMs) have revolutionized machine learning due to their ability to capture complex interactions between input features. Popular post-hoc explanation methods…
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining
Aaron J. Li, Robin Netzorg, Zhihan Cheng +2
In recent years, work has gone into developing deep interpretable methods for image classification that clearly attributes a model's output to specific features of the data. One su…