Among-LLMs

Among LLMs is a game-like OpenEnv benchmark where attacker, defender, and overseer agents interact in sabotage-style workplace tasks. It starts with deterministic, replayable episodes and reward signals, then scales into self-evolving multi-agent curricula through mutation, archival failures, and harder rollouts. The goal is to train robust oversight that detects manipulation, localizes root causes, and improves continuously via self-play-style adaptation