Avalon-M1 Trains LLMs to Form Agent Organizations via Collective-Reward RL
Avalon-M1 takes a different approach from harness-based multi-agent systems by post-training the model itself with collective-reward RL to spontaneously coordinate, raising the average score from 33.5% to 45.7%.
2026-10-28 ~ 2026-10-28 · 2 related posts
- Episode 1: General Reasoning Unveils RLCR and Avalon-M1-Mini, a 120B Model Trained as an Agent Organization(2026-10-23, 18 posts)
- Episode 2: Avalon Shows Agent Organizations Complete Tasks 4x Faster at Same Token Budget(2026-10-23, 3 posts)
- Episode 3: Avalon-M1 Trains LLMs to Form Agent Organizations via Collective-Reward RL(2026-10-28, 2 posts)
- Avalon-M1 trains LLM agent organisations via collective-reward RL, lifting avg score 33.5% to 45.7% — RobertTLange · 2026-10-28
- Avalon-M1 post-trains Nemotron 120B model to coordinate as an agent organisation — rosstaylor90 · 2026-10-28