硬件协同论文趋势 2023–2026

主要结论

• 硬件协同论文从 2023 年的 173 篇增长到 2026 年的 765 篇，三年间扩大到约 4.4 倍。
• CVPR 是发硬件协同论文最多的会议，2023–2026 年共 479 篇，占四个会议总量的 31%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 4 篇增至 2026 年的 58 篇。
• 在「效率与系统」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的数据集与基准是 2.1 倍，硬件协同是 4.4 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026AcceleGrad#: Adaptive Geometry-Aware Acceleration
• ICML 2026A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
• ICLR 2026Confident Block Diagonal Structure-Aware Invariable Graph Completion for Incomplete Multi-view Clustering
• CVPR 2026ActAvatar Temporally-Aware Precise Action Control for Talking Avatars
• NeurIPS 2025AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking
• ICML 2025CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
• ICLR 2025FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
• CVPR 2025A Distractor-Aware Memory for Visual Object Tracking with SAM2
• NeurIPS 2024HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
• ICML 2024A Universal Class of Sharpness-Aware Minimization Algorithms
• ICLR 2024Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
• CVPR 2024Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification
• NeurIPS 2023Affinity-Aware Graph Networks
• ICML 2023A Three-regime Model of Network Pruning
• ICLR 2023$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
• CVPR 20233D-Aware Face Swapping
• NeurIPS 2026Accelerating Rectified Flow Models via Trajectory-Aware Caching
• ICML 2026Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse
• ICLR 2026Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models
• CVPR 2026BD-Merging Bias-Aware Dynamic Model Merging with Evidence-Guided Contrastive Learning

全部硬件协同论文

共 45 篇，第 1 / 1 页

1. ICLR 2024A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
2. ICLR 2024Active Retrosynthetic Planning Aware of Route Quality
3. ICLR 2024Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
4. ICLR 2024Automatic Functional Differentiation in JAX
5. ICLR 2024Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
6. ICLR 2024Context-Aware Meta-Learning
7. ICLR 2024Coordinate-Aware Modulation for Neural Fields
8. ICLR 2024Curriculum reinforcement learning for quantum architecture search under hardware errors
9. ICLR 2024DAFA: Distance-Aware Fair Adversarial Training
10. ICLR 2024Data Debugging with Shapley Importance over Machine Learning Pipelines
11. ICLR 2024Data-independent Module-aware Pruning for Hierarchical Vision Transformers
12. ICLR 2024DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
13. ICLR 2024Denoising Diffusion Step-aware Models
14. ICLR 2024Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
15. ICLR 2024Discovering Temporally-Aware Reinforcement Learning Algorithms
16. ICLR 2024Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
17. ICLR 2024Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models
18. ICLR 2024EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
19. ICLR 2024Entropy-MCMC: Sampling from Flat Basins with Ease
20. ICLR 2024FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
21. ICLR 2024FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
22. ICLR 2024GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings
23. ICLR 2024Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields
24. ICLR 2024GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers
25. ICLR 2024Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
26. ICLR 2024Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
27. ICLR 2024Incentive-Aware Federated Learning with Training-Time Model Rewards
28. ICLR 2024Locality-Aware Graph Rewiring in GNNs
29. ICLR 2024LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models
30. ICLR 2024Multi-task Learning with 3D-Aware Regularization
31. ICLR 2024Principled Architecture-aware Scaling of Hyperparameters
32. ICLR 2024Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
33. ICLR 2024QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
34. ICLR 2024SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
35. ICLR 2024SaProt: Protein Language Modeling with Structure-aware Vocabulary
36. ICLR 2024Sharpness-Aware Data Poisoning Attack
37. ICLR 2024Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning
38. ICLR 2024Structural Fairness-aware Active Learning for Graph Neural Networks
39. ICLR 2024Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators
40. ICLR 2024TRAM: Bridging Trust Regions and Sharpness Aware Minimization
41. ICLR 2024Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
42. ICLR 2024Uncertainty-aware Graph-based Hyperspectral Image Classification
43. ICLR 2024Unknown Domain Inconsistency Minimization for Domain Generalization
44. ICLR 2024Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits
45. ICLR 2024Zero Bubble (Almost) Pipeline Parallelism

常见问题

2023–2026 年四大会议一共有多少篇硬件协同论文？

共 1,524 篇，按年份分别是 2023 年 173 篇、2024 年 263 篇、2025 年 323 篇、2026 年 765 篇。

NeurIPS 2026 有多少篇硬件协同论文？

NeurIPS 2026 有 263 篇硬件协同论文，上一届是 120 篇。

ICLR 2026 有多少篇硬件协同论文？

ICLR 2026 有 120 篇硬件协同论文，上一届是 44 篇。

ICML 2026 有多少篇硬件协同论文？

ICML 2026 有 186 篇硬件协同论文，上一届是 72 篇。

CVPR 2026 有多少篇硬件协同论文？

CVPR 2026 有 196 篇硬件协同论文，上一届是 87 篇。

哪个会议的硬件协同论文最多？

CVPR，2023–2026 年共 479 篇。