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cs.CL2026
SearchGym: Bootstrapping Real-World Search Agents via Cost-Effective and High-Fidelity Environment Simulation
Xichen Zhang, Ziyi He, Yinghao Zhu +6
Search agents have emerged as a pivotal paradigm for solving open-ended, knowledge-intensive reasoning tasks. However, training these agents via Reinforcement Learning (RL) faces a…
cs.CL2025
Agentar-Scale-SQL: Advancing Text-to-SQL through Orchestrated Test-Time Scaling
Pengfei Wang, Baolin Sun, Xuemei Dong +7
State-of-the-art (SOTA) Text-to-SQL methods still lag significantly behind human experts on challenging benchmarks like BIRD. Current approaches that explore test-time scaling lack…