3 papers
cs.LG2026
The Scaling Law of Evaluation Failure: Why Simple Averaging Collapses Under Data Sparsity and Item Difficulty Gaps, and How Item Response Theory Recovers Ground Truth Across Domains
Jung Min Kang
Benchmark evaluation across AI and safety-critical domains overwhelmingly relies on simple averaging. We demonstrate that this practice produces substantially misleading rankings w…
cs.SE2026
Live API-Bench: 2500+ Live APIs for Testing Multi-Step Tool Calling
Benjamin Elder, Anupama Murthi, Jungkoo Kang +4
Large language models (LLMs) increasingly rely on external tools and APIs to execute complex tasks specified in natural language. Evaluating such tool calling capabilities in reali…
cs.AI2025
Scaling LLM Planning: NL2FLOW for Parametric Problem Generation and Rigorous Evaluation
Jungkoo Kang
Robust workflow composition is critical for effective agent performance, yet progress in Large Language Model (LLM) planning and reasoning is hindered by a scarcity of scalable eva…