FlowAgent models tool chaining as continuous latent trajectory generation with conditional flow matching to deliver global planning, formal utility bounds, and better robustness on long-horizon tasks, plus a new plan-level benchmark.
Agents of change: Self-evolving llm agents for strategic planning
6 Pith papers cite this work. Polarity classification is still indexing.
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SAGE compares social co-evolution against matched self-evolution across three arenas and finds peer history enables breakthroughs only for agents that plateau under self-improvement, with abstraction of traces mattering more than raw volume.
SIGMA builds a signed relational graph among LLM agents and uses conflict-aware message passing plus weighted aggregation to produce more consistent predictions than prior cooperative-assumption baselines.
Web2BigTable introduces a bi-level multi-agent system that achieves new state-of-the-art results on wide-coverage and deep web-to-table search benchmarks through orchestration, coordination, and closed-loop reflection.
A comprehensive review of self-evolving AI agents that improve themselves over time, organized via a framework of inputs, agent system, environment, and optimizers, with domain-specific and safety discussions.
The paper delivers the first systematic review of self-evolving agents, structured around what components evolve, when adaptation occurs, and how it is implemented.
citing papers explorer
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Tools as Continuous Flow for Evolving Agentic Reasoning
FlowAgent models tool chaining as continuous latent trajectory generation with conditional flow matching to deliver global planning, formal utility bounds, and better robustness on long-horizon tasks, plus a new plan-level benchmark.
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SAGE: A Quantitative Evaluation of Socialized Evolution in Agent Ecosystems
SAGE compares social co-evolution against matched self-evolution across three arenas and finds peer history enables breakthroughs only for agents that plateau under self-improvement, with abstraction of traces mattering more than raw volume.
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Conflict-Resilient Multi-Agent Reasoning via Signed Graph Modeling
SIGMA builds a signed relational graph among LLM agents and uses conflict-aware message passing plus weighted aggregation to produce more consistent predictions than prior cooperative-assumption baselines.
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Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction
Web2BigTable introduces a bi-level multi-agent system that achieves new state-of-the-art results on wide-coverage and deep web-to-table search benchmarks through orchestration, coordination, and closed-loop reflection.
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A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
A comprehensive review of self-evolving AI agents that improve themselves over time, organized via a framework of inputs, agent system, environment, and optimizers, with domain-specific and safety discussions.
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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.