…We propose MapAgent, an industrial-grade agentic architecture that augments a vectorization backbone for specification-compliant lane-map production. Rather than merely adding an agent loop to map prediction, MapAgent couples backbone…
…This design allows agents to accumulate, select, and refine task-relevant cases , transforming past experience into actionable knowledge. Across 16 diverse tasks spanning medical diagnosis, legal analysis, code generation, web search, tool…
…An Open-Source Agentic Modeling Framework (2026) Auditing Agent Harness Safety (2026) SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety (2026) Security Risks in Tool-Enabled AI Agents: A Systematic Analysis…
…Scaling Interleaved Deliberation in Tool-Integrated Reasoning via Process-Supervised Reinforcement Learning (2026) Process Reward Agents for Steering Knowledge-Intensive Reasoning (2026) Learning Agent-Compatible Context Management for Long-Horizon Tasks (2026…
…Collaborative Agents for Dynamic Prompt Optimization in Large Language Models (2026) SPEAR: Code-Augmented Agentic Prompt Optimization (2026) Prompting Policies for Multi-step Reasoning and Tool-Use in Black-box LLMs with…
…Benchmarking Agent-as-a-Judge for Environment-Aware Evaluation (2026) AgentEscapeBench: Evaluating Out-of-Domain Tool-Grounded Reasoning in LLM Agents (2026) Terminal-World: Scaling Terminal-Agent Environments via Agent Skills (2026…
…2026) Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling (2026) Step-level Optimization for Efficient Computer-use Agents (2026) Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility…
…The reported 86% success rate across 50 solid-mechanics benchmarks suggests that agentic systems can do more than chat or code generation: they can orchestrate specialized engineering tools end to end. I…
…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…