CompoWorld: Compositional Environment Scaling for General Agents
cs.AI
Submitted: 2026-09-27
Updated: 2026-09-27
Terminology
Sources
- Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work
- Gym-Anything: Turn any Software into an Agent Environment
- Apodex 1.1: Scaling Agentic Intelligence for Complex Work
- Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
- AutoForge: Automated Environment Synthesis for Agentic Reinforcement Learning
- VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
- Scaling Agent Learning via Experience Synthesis
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
- WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation
- Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
- Towards General Agentic Intelligence via Environment Scaling
- Exposing Limitations of Language Model Agents in Sequential-Task Compositions on the Web
- Compositional Skill Routing for LLM Agents: Decompose, Retrieve, and Compose
- GLM-5: from Vibe Coding to Agentic Engineering
- VitaBench: Benchmarking LLM Agents with Versatile Interactive Tasks in Real-world Applications
- Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application
- SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks
- F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
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