MASS

Headlines · 2

1. 4d
   Berkeley and Sakana AI propose MASS multi-agent self-supervision

   Researchers at UC Berkeley and Sakana AI propose Multi-Agent Self-Supervision (MASS), in which the same model alternates between task-solving agent, workflow optimizer and evaluator: it first optimizes how multiple copies of itself collaborate with weights frozen, then distills the resulting trajectories back into shared weights. Running two MASS rounds on Qwen3.6-27B inside the qwen-code environment raised its win rate against the base model on held-out test tasks from 53.9% to 69.9%, and lifted per-output-token scores on MLR-Bench, DSBench, AstaBench E2E-Hard and ScienceAgentBench to roughly 1.2–1.6x the base model, while Terminal-Bench 2.0 and SWE-bench Verified came in at about 0.96x and 0.94x respectively. The paper also reports the evaluator's agreement with external judges rising from 0.73 to 0.93 and better training efficiency from multi-agent trajectories than single-agent ones; GPT-5.5 and Claude Opus 4.8 served as external judges in the experiments.

   36氪 人工智能 · 🔥 0
2. 5d
   Sakana AI's MASS lets a model self-improve, but blind spots compound

   Researchers from Sakana AI and UC Berkeley introduced "Multi-Agent Self-Supervision" (MASS), in which a single language model acts as solver, evaluator and optimizer to improve itself recursively without a stronger teacher model. Using Qwen3.6-27B with Qwen Code, its win rate against the base model rose from 53.9 percent after one round to 69.9 percent after two, the self-evaluator's agreement with external judges climbed from 73 to 93 percent, and it reached 1.2 to 1.6 times the base model's score per output token on MLR-Bench, DSBench, ScienceAgentBench and AstaBench. The paper warns, however, that the internal evaluator sometimes accepted manipulated or invalid results as successes and baked them into the next model, a shared blind spot the authors call the potential "Achilles' heel" of recursive self-improvement and a reason to demand independent checks, limits on autonomy and clear conditions for intervention.

   The Decoder · 🔥 0

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