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cs.AI2026
Counterfactual Regret for Reflective Agents with Lean-Verified Guarantees
Zhongnian Li, Shi Xu, Mengting Xu +2
Reflective language agents reuse feedback and memory to adapt across tasks without updating model weights. However, existing guarantees for policy selection and action generation d…
cs.AI2026
Think in Strategies, Act with Tools: Traceable Agentic Optimization for Combinatorial Problems
Zhongnian Li, Shi Xu, Peng Ying +3
Optimization by PROmpting (OPRO) directly leverages Large Language Models (LLMs) to generate candidate solutions through natural-language prompting. However, OPRO's optimization pr…