3 papers
cs.AI2026
Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments
Romain Froger, Pierre Andrews, Matteo Bettini +21
We introduce Gaia2, a benchmark for evaluating large language model agents in realistic, asynchronous environments. Unlike prior static or synchronous evaluations, Gaia2 introduces…
cs.AI2025
ARE: Scaling Up Agent Environments and Evaluations
Romain Froger, Pierre Andrews, Matteo Bettini +21
We introduce Meta Agents Research Environments (ARE), a research platform for scalable creation of environments, integration of synthetic or real applications, and execution of age…
cs.CL2025
MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Deepak Nathani, Lovish Madaan, Nicholas Roberts +14
We introduce Meta MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. This is the first Gym environment for machine…