{"total":26,"rows":[{"id":"2107.00961","title":"ResIST: Layer-Wise Decomposition of ResNets for Distributed Training","created":"2021-07-02","cited_by_count":18,"area":null},{"id":"2301.09830","title":"Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression","created":"2023-01-24","cited_by_count":15,"area":null},{"id":"2403.06664","title":"Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System","created":"2024-03-11","cited_by_count":15,"area":null},{"id":"2312.02515","title":"mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs","created":"2023-12-05","cited_by_count":12,"area":null},{"id":"2111.05972","title":"Amazon SageMaker Model Parallelism: A General and Flexible Framework for Large Model Training","created":"2021-11-10","cited_by_count":11,"area":null},{"id":"2302.00195","title":"Weight Prediction Boosts the Convergence of AdamW","created":"2023-02-01","cited_by_count":8,"area":null},{"id":"2505.18164","title":"Model-Distributed Inference for Large Language Models at the Edge","created":"2025-05-13","cited_by_count":8,"area":null},{"id":"2103.16063","title":"Automatic Graph Partitioning for Very Large-scale Deep Learning","created":"2021-03-30","cited_by_count":7,"area":null},{"id":"2206.14098","title":"RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network","created":"2022-06-28","cited_by_count":6,"area":null},{"id":"2406.02613","title":"ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training","created":"2024-06-03","cited_by_count":6,"area":null},{"id":"2505.01099","title":"Nesterov Method for Asynchronous Pipeline Parallel Optimization","created":"2025-05-02","cited_by_count":6,"area":null},{"id":"2305.18240","title":"XGrad: Boosting Gradient-Based Optimizers With Weight Prediction","created":"2023-05-26","cited_by_count":5,"area":null},{"id":"2103.08802","title":"Parareal Neural Networks Emulating a Parallel-in-time Algorithm","created":"2021-03-16","cited_by_count":4,"area":null},{"id":"2312.00839","title":"PipeOptim: Ensuring Effective 1F1B Schedule with Optimizer-Dependent Weight Prediction","created":"2023-12-01","cited_by_count":4,"area":null},{"id":"2210.16169","title":"LOFT: Finding Lottery Tickets through Filter-wise Training","created":"2022-10-28","cited_by_count":3,"area":null},{"id":"2601.22442","title":"AsyncMesh: Fully Asynchronous Optimization for Data and Pipeline Parallelism","created":"2026-01-30","cited_by_count":3,"area":null},{"id":"2302.11180","title":"DISCO: Distributed Inference with Sparse Communications","created":"2023-02-22","cited_by_count":2,"area":null},{"id":"2412.12371","title":"Priority-Aware Model-Distributed Inference at Edge Networks","created":"2024-12-16","cited_by_count":2,"area":null},{"id":"2602.03515","title":"Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation","created":"2026-02-03","cited_by_count":2,"area":null},{"id":"2605.29664","title":"AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2307.05232","title":"A Survey From Distributed Machine Learning to Distributed Deep Learning","created":"2023-07-11","cited_by_count":0,"area":null},{"id":"2309.10367","title":"Toward efficient resource utilization at edge nodes in federated learning","created":"2023-09-19","cited_by_count":0,"area":null},{"id":"2403.08837","title":"Cyclic Data Parallelism for Efficient Parallelism of Deep Neural Networks","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2604.27085","title":"Efficient Training on Multiple Consumer GPUs with RoundPipe","created":"2026-04-29","cited_by_count":0,"area":null},{"id":"2606.07881","title":"Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2606.30634","title":"One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining","created":"2026-06-29","cited_by_count":0,"area":null}],"next_cursor":null}