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Latent Compaction with Test-Time Training

Paper recorded by Signals 4 on 2026-10-14 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-14 on arXiv · recorded by Signals 4 on 2026-10-15

Category: cs.LG · 机器学习 · first seen 2026-10-15

Abstract

Long contexts enlarge key--value (KV) caches, increasing memory use and attention costs during generation. Compressing these caches must preserve information for unseen questions. We introduce **Latent Compaction**, which learns a compact document-specific cache through test-time training. We initialize cache entries using reconstruction importance, teacher attention, and key-space diversity. Trai

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#280 most recent of 749 cs.LG papers we have recorded · ↑ newer: Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Sur · ↓ older: Revisiting Simple Baselines for Relational Deep Learning
Cite this page: Latent Compaction with Test-Time Training: the #280 most recent of 749 cs.LG papers we have recorded (as of 2026-10-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/latent-compaction-with-test-time-training.html
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