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Zero training, second-level reactions (~400ms). A language-rule decision mind on a local 7B diffusion LM.

0 starsPython

Meadow Mind – a 7B diffusion LLM plays Gym games with zero training

by akaiHuang·Jun 10, 2026·2 points·0 comments
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AI Analysis

●●SolidBig BrainWizardry

Fixed-latency language-rule decisions beat traditional token-by-token LLM agents.

Strengths
  • •Zero training, zero gradients, zero reward engineering — pure language-rule inference.
  • •~400ms fixed latency regardless of decision complexity, unlike generation-based agents.
  • •Works across multiple Gym environments with single-sentence policy descriptions.
Weaknesses
  • •Zero stars, zero forks — no independent verification of benchmarks or claims.
  • •Narrow scope: only Gymnasium environments, unclear if this generalizes to real tasks.
Category
AI/ML
Target Audience

ML researchers, RL practitioners, AI hobbyists

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LLM-based RL agents · Decision Transformer · RT-1

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