No-Training Depth Boost? Recirculation Paper
teortaxesTex · x · 2026-08-19
A paper titled 'Recirculation' proposes an inference-time architectural enhancement that injects top-layer activations into bottom layers at the next step. This allows the model to act as a dynamical system to track belief states without retraining. It achieves a 23% perplexity reduction and a 21% accuracy boost on GSM8k for Gemma3, with minimal latency overhead during generation.
Related event: DeepMind's Recirculation boosts LLM reasoning without retraining(10 posts)→
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