…Experiments on four benchmarks demonstrate that TacoMAS outperforms nearly 20 multi-agent baselines, achieving an average improvement of 13.3% over the strongest baseline. Get this paper in your agent: hf papers…
…Xinyu Lu , , , , , , , , , , Abstract The Meta-Agent Challenge evaluates AI models' ability to autonomously develop agent systems through iterative programming within constrained environments, revealing significant gaps in current models' self-improvement capabilities. Generated…
…TMAS improves test-time scaling by turning independent reasoning rollouts into a coordinated multi-agent process, where agents verify, summarize, reuse reliable experience, avoid redundant strategies, and are further aligned through hybrid…
…Multi-agent systems using large language models suffer from inefficient token consumption in agent-to-agent communication, which PACT addresses by structuring messages as compact action-state records that improve performance-cost…
…We then perform Tool-Bootstrapped GUI RFT , combining warmup SFT with single-turn RL to improve decisions at critical GUI-Tool switching points. Finally, we optimize ToolCUA with Online Agentic RL in…
…Ning Lu , , , , , , , , , , , Abstract PaW is a co-training framework that combines policy learning and world modeling using on-policy reinforcement learning rollouts to improve language agent training without additional computational overhead. Generated…
Papers arxiv:2605.02943 Healthcare AI GYM for Medical Agents Published on May 1 Submitted by Minbyul Jeong on May 6 Authors: Abstract Multi-turn clinical reasoning training using reinforcement learning reveals…
…introducing trajectory-level strategies that improve sample efficiency and performance across interactive environments. AI-generated summary Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon…
…Abstract AgensFlow is an open-source framework that treats multi-agent coordination as an online policy-learning problem under partial observability, enabling learned routing to improve coordination-heavy workflows over static approaches…
…Qiliang Liang , , , Abstract Structured representation of agent skills disentangles scheduling, execution, and logic components, improving performance in skill discovery and risk assessment tasks. AI-generated summary LLM agents increasingly rely on reusable…