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Online Label-Free Gradient Matching for Continual Language Model Training

Paper recorded by Signals 4 on 2026-11-02 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-02 on arXiv · recorded by Signals 4 on 2026-11-03

Category: cs.CL · 自然语言处理 · first seen 2026-11-03

Abstract

Language models in customer-facing products must be continually updated, since the data they serve shifts over time. As retraining on the full accumulated data is impractical, each update should instead run on a small set of examples carrying the training signal of all data seen so far. The strongest current methods build this set by gradient matching, which synthesizes examples whose training gra

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#15 most recent of 628 cs.CL papers we have recorded · ↑ newer: VIAS: Value-Isolating Activation Steering for Multi-Value Alignment an · ↓ older: Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self
Cite this page: Online Label-Free Gradient Matching for Continual Language Model Training: the #15 most recent of 628 cs.CL papers we have recorded (as of 2026-11-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/online-label-free-gradient-matching-for-continual-language-model-training.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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