ZeroLock: Concurrent Memory-Efficient LLM Training via Modular Update Decoupling

arXiv:2608.07974 · cs.LG, cs.DC · Submitted 2026-08-08 · Read on arXiv

Wentao Dai, Xuanran Li, Yuxiang Zhang, Ming Tang, Chao Huang

cs.LG, cs.DC

Submitted: 2026-08-08

Updated: 2026-08-11

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

Terminology

• Fine-Tuning — 19× in this paper · explained in 5 episodes
• Decoupling — 10× in this paper · explained in 2 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Frozen model — 3× in this paper · explained in 3 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Predictive Coding — 2× in this paper · explained in 3 episodes
• Communication Efficiency — 1× in this paper · explained in 2 episodes
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 9 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Federated Learning — 1× in this paper · explained in 19 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• Remote Procedure Call — 1× in this paper
• Robustness — 1× in this paper · explained in 6 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Zeroth-Order Optimization — 1× in this paper · explained in 2 episodes

Sources

• End-to-End Test-Time Training for Long Context
• CollaPipe: Adaptive Segment-Optimized Pipeline Parallelism for Collaborative LLM Training in Heterogeneous Edge Networks
• Faster Multi-GPU Training with PPLL: A Pipeline Parallelism Framework Leveraging Local Learning
• Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training

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