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As Large Language Models (LLMs) evolve, parallel reasoning has emerged as a vital inference paradigm that enhances robustness by concurrently exploring multiple thought trajectories. Unlike fragile sequential methods, parallel reasoning expands inference breadth to significantly improve problem-solving performance. T...
This paper proposes CRISP, a framework for training efficient deep search agents through critical step perception that distinguishes interactions that gather necessary evidence from redundant ones and shapes the training reward to preserve the former while pruning the latter, improving efficiency without sacrificing th...
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