Residual Vector-based Reconstruction as Long-Context Recall Regardless of Context Window Size
Paper recorded by Signals 4 on 2026-09-11 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-11 on arXiv · recorded by Signals 4 on 2026-09-14
Category: cs.CL · 自然语言处理 · first seen 2026-09-14
Abstract
Large language models (LLMs) process long contexts, including long documents and lengthy conversations, but face token-level memory usage that increases proportionally to input length. Although model optimization and lossy prompt compression are widely used, these methods still fail to solve the long-context recall problem beyond pretrained and size-constrained context windows. This paper proposes
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Cite this page: Residual Vector-based Reconstruction as Long-Context Recall Regardless of Context Window Size: the #64 most recent of 186 cs.CL papers we have recorded (as of 2026-09-11). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/residual-vector-based-reconstruction-as-long-context-recall-regardless-of-contex.html
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