Researcher, AGI, Inc.
2 papers at NeurIPS 2025
We propose to scale the number of interaction steps for agents as a new axis of test-time scaling and develop a curriculum-based online RL algorithm for training agents to scale interaction.
Ultra-realistic benchmark environments and evaluation framework for web agents