ChainLoRA: Geometry-Preserving Task Vector Merging for Continual Learning in LLMs

arXiv:2610.00431 · stat.ML, cs.LG · Submitted 2026-09-30 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-30

Updated: 2026-09-30

Comments: 18 pages

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Continual Learning — 25× in this paper · explained in 2 episodes
• Adaptation — 24× in this paper · explained in 1 episode
• Benchmark — 13× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 9× in this paper · explained in 5 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Parameter-Efficient Fine-Tuning — 3× in this paper · explained in 2 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Entanglement — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Intrinsic Dimension — 2× in this paper · explained in 2 episodes
• Model Merging — 2× in this paper · explained in 2 episodes
• Parameter Efficiency — 2× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Stiefel manifold — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging
• Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

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