…Holistic Trajectory-Level Evaluation of LLM Tool Calling for Long-Horizon Financial Tasks (2026) The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break (2026) AJ-Bench: Benchmarking Agent-as…
…AI-generated summary Reinforcement learning for agentic large language models (LLMs) typically relies on a sparse, trajectory-level outcome reward , making it difficult to evaluate the contribution of individual tool-calls within…
…We ground the framework with case studies in math, code/SQL, multimodal reasoning, tool-using agents, and agentic skill benchmarks that evaluate skill induction, reuse, and cross-task transfer. Finally, we provide…
…Observability-Driven Automatic Evolution of Coding-Agent Harnesses (2026) Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use (2026) Continual Harness: Online Adaptation for Self-Improving Foundation Agents (2026) RoboPhD…
…While recent general-domain tool-calling datasets have substantially improved the capabilities of LLM agents, existing efforts in the biomedical domain largely rely on in-context learning and restrict models to a…
…AI-generated summary Large Language Model (LLM)-based agents have fundamentally reshaped artificial intelligence by integrating external tools and planning capabilities. While memory mechanisms have emerged as the architectural cornerstone of these…
…Computer-Use Agents Learning Professional Skills via Exploration (2026) EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings (2026) OccuBench: Evaluating AI Agents on Real-World…
…this line up with differentiable simulation and tool-use work, and a direct comparison here could clarify what external planning actually buys on real visual tasks. Get this paper in your agent…
Papers arxiv:2606.04703 Rethinking Continual Experience Internalization for Self-Evolving LLM Agents Published on Jun 3 Submitted by Wenkai Yang on Jun 5 Authors: Jingwen Chen , Wenkai Yang , , , , , , , , Abstract Experience internalization…
…A General RL Optimization Framework for LLM-Based Multi-Agent Systems (2026) Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility, Cost, and Bottlenecks in Multi-Agent Workflows (2026) A Comprehensive…