2 papers
cs.CL2026
Conv-to-Bench: Evaluating Language Models Via User-Assistant Dialogues In Code Tasks
Victor M. dos Santos, Andre C. Castro, Samuel L. de S. Toledo +5
The rapid advancement of Large Language Models (LLMs) has outpaced the scalability of traditional evaluation benchmarks, which remain heavily dependent on labor-intensive expert cu…
cs.LG2026
Do Reasoning Models Ask Better Questions? A Formal Information-Theoretic Analysis on Multi-Turn LLM Games
Daniel M. Pedrozo, Telma W. de L. Soares, Bryan L. M. de Oliveira
Large Language Models (LLMs) excel at many tasks but still struggle with a critical ability for LLM-based agents: asking good questions for resolving ambiguity in user requests. Wh…