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Atria Dawn Preview is introduced, a foundation agentic language model designed for scientific research and engineering workflows, with the goal of expanding the frontier of agent productivity in the real world.
This paper proposes Disentangled Action--Reasoning Tuning (DART), a simple and efficient framework that explicitly decouples parameter updates for reasoning and tool use via separate low-rank adaptation modules, further supporting the finding of capability interference under shared optimization.
This work presents a training-free framework that formulates SQL correction as a plan-guided, tree-structured debugging process that mitigates error accumulation during iterative refinement and demonstrates the effectiveness and stability of the approach in real-world deployments.
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