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cs.LG2026
COMPASS: Benchmarking Constrained Optimization in LLM Agents
Tian Qin, Felix Bai, Ting-Yao Hu +8
Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shopping, and scheduling, they must…
cs.LG2026★ 1 cited
EvoX: Meta-Evolution for Automated Discovery
Shu Liu, Shubham Agarwal, Monishwaran Maheswaran +14
Recent work such as AlphaEvolve has shown that combining LLM-driven optimization with evolutionary search can effectively improve programs, prompts, and algorithms across domains.…
cs.LG2024
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
Hao Bai, Yifei Zhou, Mert Cemri +4
Training corpuses for vision language models (VLMs) typically lack sufficient amounts of decision-centric data. This renders off-the-shelf VLMs sub-optimal for decision-making task…