"Adversarial Speculative Reasoning Improves Long Horizon Agents"
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"Adversarial Speculative Reasoning Improves Long Horizon Agents" Speculative decoding normally speeds up LLM inference, but this paper finds that numerical noise increases by roughly 4% per position within a verification block, potentially affecting critical decisions in long-horizon agent tasks. So they proposed Adversarial Speculative Reasoning that deliberately trains the draft model to disagree with the target at important reasoning decisions, triggering rejection and restarting verification at a more numerically precise position. On DeepSWE, this improves GLM-5.3's success rate from 60
Posted by alphaXiv (60.5k followers) 1 days ago · 122 likes · 5.3k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: alphaXiv.
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