ProgAgent: Learning Tool Orchestration through Programmatic Training
cs.AI
Submitted: 2026-10-10
Updated: 2026-10-10
Code: https://github.com/containers/bubblewrap
Sources
- MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers
- Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
- A Theory of Universal Artificial Intelligence based on Algorithmic Complexity
- The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution
- Simulating Environments with Reasoning Models for Agent Training
- The Bitter Lesson of Tool Calling
- Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
- EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis
- SWE-World: Building Software Engineering Agents in Docker-Free Environments
- AgentSkiller: Scaling Generalist Agent Intelligence through Semantically Integrated Cross-Domain Data Synthesis
- Qwen3 Technical Report
- ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
- Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning
- MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use
- WebWorld: A Large-Scale World Model for Web Agent Training
- EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL
- TOUCAN: Synthesizing 1.5M Tool-Agentic Data from Real-World MCP Environments
- LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems