2 papers
cs.CL2025
Agent-RLVR: Training Software Engineering Agents via Guidance and Environment Rewards
Jeff Da, Clinton Wang, Xiang Deng +3
Reinforcement Learning from Verifiable Rewards (RLVR) has been widely adopted as the de facto method for enhancing the reasoning capabilities of large language models and has demon…
cs.AI2025
EnigmaEval: A Benchmark of Long Multimodal Reasoning Challenges
Clinton J. Wang, Dean Lee, Cristina Menghini +7
As language models master existing reasoning benchmarks, we need new challenges to evaluate their cognitive frontiers. Puzzle-solving events are rich repositories of challenging mu…