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COMPANY · ENTITY #441

ReAct

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RESEARCH · 1 SOURCE · arXiv cs.AI

DeReAct paper: modular Critic and Context Manager for more reliable ReAct-style agents

The arXiv preprint introduces DeReAct, a modular agent architecture that externalizes two gating policies—a Critic to validate proposed actions and a Context Manager to reconstruct environment-supported state and certify task completion. On GAIA and SWE-bench Verified, DeReAct raises Pass@1 most for weaker "Brain" models (6.5–7.0 points for Qwen3-Coder-480B, 4.2–5.2 points for Claude Sonnet 4.5), with smaller gains as model capability increases; with Claude Opus 4.5 overall Pass@1 is comparable to ReAct but trajectories are more evidence-complete and constraint-satisfying.

7.0

RESEARCH · 1 SOURCE · arXiv cs.AI

AutoTailor: Automatic, user-aligned capability selection and adaptation for web agents

AutoTailor is a meta-agentic framework that converts web interaction trajectories into parameterized browser-automation APIs, applies offline Quality and Usage Likelihood filters to remove redundant or low-value APIs, and uses online Dynamic Reselection to add missing capabilities and prune persistently unused ones. Evaluated on 106 WebArena Postmill tasks, offline filtering reduced 1,283 initial APIs to 87 and Dynamic Reselection yielded a 33-API set; with a ReAct fallback this set achieved 90.6% correctness (vs. 87.5% for ReAct alone) while cutting request-token cost by 57.8% and latency by 29.4%, and without ReAct it reached 60.1% correctness while reducing request-token usage by 94.9%.

7.0