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Language Models Can Control Their Own Attention

Paper recorded by Signals 4 on 2026-09-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-02 on arXiv · recorded by Signals 4 on 2026-09-03

Category: cs.AI · 人工智能 · first seen 2026-09-03

Abstract

Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If the user asks about a previous detail in a 1M-token conversation, global attention layers must scan the full context to generate each token of the reply. A prominent approach mitigates this cost by pre-selecting relevant tokens via lightweight proxy

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#215 most recent of 300 cs.AI papers we have recorded · ↑ newer: HiPoly: a hierarchical polymer-native AI framework for property predic · ↓ older: RVSD: Retrieval Vision Sparse Decoding for Mitigating Visual Hallucina
Cite this page: Language Models Can Control Their Own Attention: the #215 most recent of 300 cs.AI papers we have recorded (as of 2026-09-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/language-models-can-control-their-own-attention.html
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