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Sync authorship note

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  **Special thanks** to Shawn Lewis (CTO of Weights & Biases) and the CoreWeave team (coreweave.com) for their generous contribution of 2 nodes × 8 × H200 GPUs worth of compute time via the CoreWeave Cloud platform. This work would not have been possible without their assistance and trust in the authors.
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  ## Model Summary
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  - **Architecture**: Tiny Recursive Model (TRM) with ACT V1 controller
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  `L_layers=2`, `H_cycles=3`, `L_cycles=4`, hidden size 512, 8 heads, RoPE positional encodings, bfloat16 activations.
 
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  **Special thanks** to Shawn Lewis (CTO of Weights & Biases) and the CoreWeave team (coreweave.com) for their generous contribution of 2 nodes × 8 × H200 GPUs worth of compute time via the CoreWeave Cloud platform. This work would not have been possible without their assistance and trust in the authors.
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+ **Note on authorship.** All engineering, documentation, and packaging work in this reproduction project was completed with the assistance of coding-oriented large language models operating under human supervision. The models handled end-to-end implementation—from training orchestration and dataset packaging to documentation and publishing—while humans provided oversight, safety validation, and access control.
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  ## Model Summary
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  - **Architecture**: Tiny Recursive Model (TRM) with ACT V1 controller
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  `L_layers=2`, `H_cycles=3`, `L_cycles=4`, hidden size 512, 8 heads, RoPE positional encodings, bfloat16 activations.