SETA: Scaling Environments for Terminal Agents

arXiv:2607.10891 · cs.AI · Submitted 2026-07-12 · Read on arXiv

cs.AI

Submitted: 2026-07-12

Updated: 2026-09-30

Code: https://github.com/camel-ai/seta

Project page: https://www.compilebench.com

Terminology

• Verification — 2× in this paper · explained in 2 episodes
• Agent Harness — 1× in this paper · explained in 2 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Sources

• DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
• AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
• Endless Terminals: Scaling RL Environments for Terminal Agents
• R2E-Gym: Procedural Environments and Hybrid Verifiers for Scaling Open-Weights SWE Agents
• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
• CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation
• Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
• Training Software Engineering Agents and Verifiers with SWE-Gym
• On Data Engineering for Scaling LLM Terminal Capabilities
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
• ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
• Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environments
• OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
• SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
• SWE-smith: Scaling Data for Software Engineering Agents
• ReAct: Synergizing Reasoning and Acting in Language Models
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale
• RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
• WebArena: A Realistic Web Environment for Building Autonomous Agents

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