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cs.AI2026
Verifier-Harness Co-Evolution for Training-Free Self-Improvement on Open-Ended Tasks
Tianyi Xu, Yaolun Zhang, Yiran Wu +6
Training-free self-improvement lets an agent use feedback to revise the response it is about to return and to update the harness state that shapes how it handles later tasks. On op…
cs.AI2026
Infeasibility Aware Large Language Models for Combinatorial Optimization
Yakun Wang, Min Chen, Zeguan Wu +3
Large language models (LLMs) are increasingly explored for NP-hard combinatorial optimization problems, but most existing methods emphasize feasible-instance solution generation an…