A Compile-and-Execute system decouples LLM reasoning from browser execution via a one-shot JSON blueprint, reducing inference from O(M x N) to amortized O(1) for repetitive web workflows.
Explorer: Scaling exploration-driven web trajectory synthesis for multimodal web agents
3 Pith papers cite this work. Polarity classification is still indexing.
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DynaWeb introduces a model-based RL framework that trains web agents via imagined rollouts in a learned web world model interleaved with real expert trajectories, yielding consistent gains on WebArena and WebVoyager benchmarks.
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Agentic Compilation: Mitigating the LLM Rerun Crisis for Minimized-Inference-Cost Web Automation
A Compile-and-Execute system decouples LLM reasoning from browser execution via a one-shot JSON blueprint, reducing inference from O(M x N) to amortized O(1) for repetitive web workflows.
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DynaWeb: Model-Based Reinforcement Learning of Web Agents
DynaWeb introduces a model-based RL framework that trains web agents via imagined rollouts in a learned web world model interleaved with real expert trajectories, yielding consistent gains on WebArena and WebVoyager benchmarks.
- A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications