Token-Gated Language Models learn to skim context for up to 11x faster LLM prefill
CShorten30 · x · 2026-10-23
Liana Patel's team introduced Token-Gated Language Models (TokenGate): end-to-end learning to 'skim' context during prefill, conditionally forwarding only the tokens that matter, for up to 11x faster prefill.
- Framed as analogous to the dense-models-to-MoE shift, extending conditional computation to a new scaling axis: context tokens
- Echoes prior work on decision models and prefill optimization; commenters see on-the-fly token dropping as a new frontier for efficient LLMs
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