Action Semantics Learning trains app agents to align with the semantic effects of actions via a Semantic Estimator module, improving robustness to out-of-distribution scenarios over syntax-matching fine-tuning.
Distrl: An asynchronous distributed reinforcement learning framework for on-device control agents
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The paper delivers the first systematic review of self-evolving agents, structured around what components evolve, when adaptation occurs, and how it is implemented.
A survey consolidating frameworks, data practices, large action models, benchmarks, applications, and research gaps in LLM-brained GUI agents.
citing papers explorer
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Beyond Syntax: Action Semantics Learning for App Agents
Action Semantics Learning trains app agents to align with the semantic effects of actions via a Semantic Estimator module, improving robustness to out-of-distribution scenarios over syntax-matching fine-tuning.
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A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence
The paper delivers the first systematic review of self-evolving agents, structured around what components evolve, when adaptation occurs, and how it is implemented.
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Large Language Model-Brained GUI Agents: A Survey
A survey consolidating frameworks, data practices, large action models, benchmarks, applications, and research gaps in LLM-brained GUI agents.