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NeurIPS 2026Allen Institute for AIAi2 / TTICTokenization

Comparing Transformers and Hybrid Models at the Token Level

Yanhong Li, Will Merrill

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026U ChicagoToyota Technological Institute aAllen Institute for AITTI-ChicagoStony BrookEfficient inference & serving

Distilling Sequential Computation in Transformer Language Models

A lightweight merge module replaces token spans with surrogate embeddings, cutting Transformer sequence lengths by up to 40% with minimal accuracy loss and no retraining.

Zixuan Lan, Jessica Yang, Yanhong Li, Karen Livescu and 1 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5