Distributed Training papers, 2023–2026

Key findings

• Distributed Training went from 95 papers in 2023 to 98 in 2026, roughly 1.0x in three years.
• NeurIPS publishes the most Distributed Training work: 208 papers from 2023 to 2026, 53% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 1 in 2023 to 10 in 2026.
• Among the 5 topics under Efficiency and Systems, it ranks #4 by 2026 paper count; the fastest grower in the group, Hardware-Aware ML, is up 4.4x versus 1.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026AgentWeave: Efficient Distributed Agent Serving via Flow Decomposition
• ICML 2026Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
• ICLR 2026Cascadia: An Efficient Cascade Serving System for Large Language Models
• CVPR 2026Finding Distributed Object-Centric Properties in Self-Supervised Transformers
• NeurIPS 2025A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments
• ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
• ICLR 2025Addressing Label Shift in Distributed Learning via Entropy Regularization
• CVPR 2025Real-time High-fidelity Gaussian Human Avatars with Position-based Interpolation of Spatially Distributed MLPs
• NeurIPS 2024Communication Efficient Distributed Training with Distributed Lion
• ICML 2024Embarrassingly Parallel GFlowNets
• ICLR 2024Benchmarking Algorithms for Federated Domain Generalization
• CVPR 2024Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations
• NeurIPS 20232Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression
• ICML 2023Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures
• ICLR 2023Distributed Extra-gradient with Optimal Complexity and Communication Guarantees
• CVPR 2023DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training
• NeurIPS 2026Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods
• ICML 2026Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers
• ICLR 2026DualMap: Enabling Both Cache Affinity and Load Balancing for Distributed LLM Serving
• CVPR 2026Parallel Rigidity Matters for Bundle Adjustment

All Distributed Training papers

40 papers, page 1 of 1

1. ICML 2025Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks
2. ICML 2025Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
3. ICML 2025ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
4. ICML 2025Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
5. ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
6. ICML 2025Causality Inspired Federated Learning for OOD Generalization
7. ICML 2025Deep Streaming View Clustering
8. ICML 2025Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
9. ICML 2025Distributed Conformal Prediction via Message Passing
10. ICML 2025Distributed Event-Based Learning via ADMM
11. ICML 2025Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal
12. ICML 2025Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance Learning
13. ICML 2025Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold
14. ICML 2025DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers
15. ICML 2025DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence
16. ICML 2025Efficient Distributed Optimization under Heavy-Tailed Noise
17. ICML 2025Efficiently Serving Large Multimodal Models Using EPD Disaggregation
18. ICML 2025Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
19. ICML 2025FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
20. ICML 2025FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation
21. ICML 2025HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
22. ICML 2025How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical Perspective
23. ICML 2025Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
24. ICML 2025Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging
25. ICML 2025Layer-wise Quantization for Quantized Optimistic Dual Averaging
26. ICML 2025Learning curves theory for hierarchically compositional data with power-law distributed features
27. ICML 2025LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
28. ICML 2025Nesterov Method for Asynchronous Pipeline Parallel Optimization
29. ICML 2025On Fine-Grained Distinct Element Estimation
30. ICML 2025On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
31. ICML 2025Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
32. ICML 2025Riemannian Diffusion Adaptation for Distributed Optimization on Manifolds
33. ICML 2025Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
34. ICML 2025Safe-EF: Error Feedback for Non-smooth Constrained Optimization
35. ICML 2025Scalable First-order Method for Certifying Optimal k-Sparse GLMs
36. ICML 2025Shortcut-connected Expert Parallelism for Accelerating Mixture of Experts
37. ICML 2025SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
38. ICML 2025The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
39. ICML 2025Unified Breakdown Analysis for Byzantine Robust Gossip
40. ICML 2025When, Where and Why to Average Weights?

FAQ

How many Distributed Training papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

396 in total: 95 in 2023, 74 in 2024, 129 in 2025, 98 in 2026.

How many Distributed Training papers are at NeurIPS 2026?

NeurIPS 2026 has 36 Distributed Training papers, versus 69 the year before.

How many Distributed Training papers are at ICLR 2026?

ICLR 2026 has 18 Distributed Training papers, versus 18 the year before.

How many Distributed Training papers are at ICML 2026?

ICML 2026 has 42 Distributed Training papers, versus 40 the year before.

How many Distributed Training papers are at CVPR 2026?

CVPR 2026 has 2 Distributed Training papers, versus 2 the year before.

Which conference publishes the most Distributed Training papers?

NeurIPS, with 208 papers from 2023 to 2026.