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Adaptive Multi-Token Prediction: How far should we go?

Paper recorded by Signals 4 on 2026-10-20 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-20 on arXiv · recorded by Signals 4 on 2026-10-21

Category: cs.AI · 人工智能 · first seen 2026-10-21

Abstract

Multi-token prediction (MTP) can accelerate language-model decoding by drafting several tokens and verifying them in a single target-model pass. However, the best speculation horizon changes with context: longer drafts offer greater amortization when reliable, but can waste compute on suffixes discarded after a rejection. Unlike autoregressive drafting, where a stopping rule can decide token by to

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#226 most recent of 960 cs.AI papers we have recorded · ↑ newer: MindView: Benchmarking Generative Multi-View Spatial Intelligence · ↓ older: Semantic Observability for Autonomous Systems Diagnostics

Cite this page: Adaptive Multi-Token Prediction: How far should we go?: the #226 most recent of 960 cs.AI papers we have recorded (as of 2026-10-20). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/adaptive-multi-token-prediction-how-far-should-we-go.html
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