Hardware-Aware ML papers, 2023–2026

Accelerators and compilation

Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,524 papers are tagged with this topic.

Key findings

Papers per year

Papers per venue

Counts by year and venue

Hardware-Aware ML papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
2023212327102173
202469455594263
2025120447287323
2026263120186196765

Representative papers

Spread across years and venues so every edition shows up

All Hardware-Aware ML papers

1,524 papers, page 6 of 31

  1. ICLR 2026Hyperbolic Aware Minimization: Implicit Bias for Sparsity
  2. ICLR 2026IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring
  3. ICLR 2026Imitating the Truth: Attention-aware Truth-Guided Enhancement for Hallucination Mitigation in Large Vision-Language Models
  4. ICLR 2026Keep the Best, Forget the Rest: Reliable Alignment with Order-Aware Preference Optimization
  5. ICLR 2026Knowledge Editing with Subspace-Aware Key-Value Mappings
  6. ICLR 2026LANE: Label-Aware Noise Elimination for Fine-Grained Text Classification
  7. ICLR 2026Language Confusion Gate: Language-Aware Decoding Through Model Self-Distillation
  8. ICLR 2026Learning Part-Aware Dense 3D Feature Field For Generalizable Articulated Object Manipulation
  9. ICLR 2026Learning Semi-Structured Sparsity for LLMs via Shared and Context-Aware Hypernetwork
  10. ICLR 2026Lipschitz Bandits with Stochastic Delayed Feedback
  11. ICLR 2026MAVEN: A Mesh-Aware Volumetric Encoding Network for Simulating 3D Flexible Deformation
  12. ICLR 2026Membership Privacy Risks of Sharpness Aware Minimization
  13. ICLR 2026MergOPT: A Merge-Aware Optimizer for Robust Model Merging
  14. ICLR 2026Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization
  15. ICLR 2026Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting
  16. ICLR 2026NDAD: Negative-Direction Aware Decoding for Large Language Models via Controllable Hallucination Signal Injection
  17. ICLR 2026Neuron-Aware Data Selection in Instruction Tuning for Large Language Models
  18. ICLR 2026Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization
  19. ICLR 2026Non-Convex Federated Optimization under Cost-Aware Client Selection
  20. ICLR 2026OWL : Geometry-Aware Spatial Reasoning for Audio Large Language Models
  21. ICLR 2026Paper Copilot: Tracking the Evolution of Peer Review in AI Conferences
  22. ICLR 2026PEAR: Phase Entropy Aware Reward for Efficient Reasoning
  23. ICLR 2026PRISM: Festina Lente Proactivity—Risk-Sensitive, Uncertainty-Aware Deliberation for Proactive Agents
  24. ICLR 2026Quantization-Aware Diffusion Models For Maximum Likelihood Training
  25. ICLR 2026QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models
  26. ICLR 2026RADAR: Learning to Route with Asymmetry-aware Distance Representations
  27. ICLR 2026RADAR: Reasoning–Ability and Difficulty-Aware Routing in Language Models
  28. ICLR 2026RankFlow: Property-aware Transport for Protein Optimization
  29. ICLR 2026Relationship Alignment for View-aware Multi-view Clustering
  30. ICLR 2026Rényi Sharpness: A Novel Sharpness that Strongly Correlates with Generalization
  31. ICLR 2026RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility
  32. ICLR 2026Revisiting Sharpness-Aware Minimization: A More Faithful and Effective Implementation
  33. ICLR 2026Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
  34. ICLR 2026SAQ: Stabilizer-Aware Quantum Error Correction Decoder
  35. ICLR 2026SCAD: Super-Class-Aware Debiasing for Long-Tailed Semi-Supervised Learning
  36. ICLR 2026Secure Outlier-Aware Large Language Model Inference
  37. ICLR 2026Sem-MoE: Semantic-aware Model-Data Collaborative Scheduling for Efficient MoE Inference
  38. ICLR 2026Semantic-Aware Diffusion LLM Inference With Adaptive Block Size
  39. ICLR 2026Semantic-aware Wasserstein Policy Regularization for Large Language Model Alignment
  40. ICLR 2026SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization
  41. ICLR 2026SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration
  42. ICLR 2026Sharpness-Aware Machine Unlearning
  43. ICLR 2026Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization
  44. ICLR 2026SNaX: sparse narrow accelerated mixture of experts
  45. ICLR 2026SONA: Learning Conditional, Unconditional, and Matching-Aware Discriminator
  46. ICLR 2026SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism
  47. ICLR 2026Splat and Distill: Augmenting Teachers with Feed-Forward 3D Reconstruction For 3D-Aware Distillation
  48. ICLR 2026Steering Evaluation-Aware Language Models To Act Like They Are Deployed
  49. ICLR 2026Symmetry-Aware Bayesian Optimization via Max Kernels
  50. ICLR 2026Task-Aware Data Selection via Proxy-Label Enhanced Distribution Matching for LLM Finetuning

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FAQ

How many Hardware-Aware ML papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
1,524 in total: 173 in 2023, 263 in 2024, 323 in 2025, 765 in 2026.
How many Hardware-Aware ML papers are at NeurIPS 2026?
NeurIPS 2026 has 263 Hardware-Aware ML papers, versus 120 the year before.
How many Hardware-Aware ML papers are at ICLR 2026?
ICLR 2026 has 120 Hardware-Aware ML papers, versus 44 the year before.
How many Hardware-Aware ML papers are at ICML 2026?
ICML 2026 has 186 Hardware-Aware ML papers, versus 72 the year before.
How many Hardware-Aware ML papers are at CVPR 2026?
CVPR 2026 has 196 Hardware-Aware ML papers, versus 87 the year before.
Which conference publishes the most Hardware-Aware ML papers?
CVPR, with 479 papers from 2023 to 2026.

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