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This work proposes DualSQL, a new Text-to-SQL system consisting of two agents powered by a single model backbone, enabling joint optimization through a robust multi-agent reinforcement learning (RL) framework, and introduces a new SQL correctness metric, robust execution match (REX), to more accurately judge SQL correctness and assign reward signals.
By reallocating KV cache resources based on attention head specialization, SGD-KV cuts memory usage by 75% while handling contexts up to 1M tokens with state-of-the-art accuracy.
