通用机器学习 · evaluation论文趋势 2023–2026

主要结论

• 通用机器学习 · evaluation论文从 2023 年的 53 篇增长到 2026 年的 230 篇，三年间扩大到约 4.3 倍。
• NeurIPS 是发通用机器学习 · evaluation论文最多的会议，2023–2026 年共 270 篇，占四个会议总量的 45%。
• 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 47 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 4；同组增长最快的通用机器学习 · reinforcement learning是 2.0 倍，通用机器学习 · evaluation是 4.3 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 2026AI Construct Lexis: An Ontology of the Hidden Assumptions in AI Evaluation
• ICML 2026A Computational Framework for Evaluating Human-likeness in LLMs' Open-ended Human Behaviors
• ICLR 2026Unlearning Evaluation through Subset Statistical Independence
• CVPR 2026Bridging the Perception Gap in Image Super-Resolution Evaluation
• NeurIPS 2025Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search
• ICML 2025AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings
• ICLR 2025On Speeding Up Language Model Evaluation
• CVPR 2025ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
• NeurIPS 2024Accuracy is Not All You Need
• ICML 2024A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models
• ICLR 2024BatchPrompt: Accomplish more with less
• CVPR 2024Animating General Image with Large Visual Motion Model
• NeurIPS 2023AQuA: A Benchmarking Tool for Label Quality Assessment
• ICML 2023Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
• ICLR 2023Beyond calibration: estimating the grouping loss of modern neural networks
• CVPR 2023GeneCIS: A Benchmark for General Conditional Image Similarity
• NeurIPS 2026AMUSE: Anytime Muon with Stable Gradient Evaluation
• ICML 2026A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems
• ICLR 2026Choices Speak Louder than Questions
• CVPR 2026Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks

全部通用机器学习 · evaluation论文

共 53 篇，第 1 / 2 页

1. CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
2. CVPR 2023Beyond mAP: Towards Better Evaluation of Instance Segmentation
3. CVPR 2023BiasBed - Rigorous Texture Bias Evaluation
4. CVPR 2023GeneCIS: A Benchmark for General Conditional Image Similarity
5. CVPR 2023GP-VTON: Towards General Purpose Virtual Try-On via Collaborative Local-Flow Global-Parsing Learning
6. CVPR 2023Neuralizer: General Neuroimage Analysis Without Re-Training
7. CVPR 2023PMR: Prototypical Modal Rebalance for Multimodal Learning
8. ICLR 2023A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
9. ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
10. ICLR 2023Agnostic Learning of General ReLU Activation Using Gradient Descent
11. ICLR 2023Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
12. ICLR 2023Backstepping Temporal Difference Learning
13. ICLR 2023Beyond calibration: estimating the grouping loss of modern neural networks
14. ICLR 2023Continual evaluation for lifelong learning: Identifying the stability gap
15. ICLR 2023Evaluating Representations with Readout Model Switching
16. ICLR 2023General Neural Gauge Fields
17. ICLR 2023MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
18. ICLR 2023Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN
19. ICLR 2023NERDS: A General Framework to Train Camera Denoisers from Raw-RGB Noisy Image Pairs
20. ICLR 2023Single-shot General Hyper-parameter Optimization for Federated Learning
21. ICLR 2023Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
22. ICLR 2023Stochastic No-regret Learning for General Games with Variance Reduction
23. ICLR 2023The Role of ImageNet Classes in Fréchet Inception Distance
24. ICLR 2023Variational Latent Branching Model for Off-Policy Evaluation
25. ICML 2023An Instrumental Variable Approach to Confounded Off-Policy Evaluation
26. ICML 2023Dimensionality Reduction for General KDE Mode Finding
27. ICML 2023Distributional Offline Policy Evaluation with Predictive Error Guarantees
28. ICML 2023Explainability as statistical inference
29. ICML 2023FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels
30. ICML 2023General Covariance Data Augmentation for Neural PDE Solvers
31. ICML 2023Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
32. ICML 2023Neural Status Registers
33. ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
34. ICML 2023Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
35. ICML 2023VIMA: Robot Manipulation with Multimodal Prompts
36. NeurIPS 2023A General Framework for Robust G-Invariance in G-Equivariant Networks
37. NeurIPS 2023AQuA: A Benchmarking Tool for Label Quality Assessment
38. NeurIPS 2023Beyond Average Return in Markov Decision Processes
39. NeurIPS 2023Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
40. NeurIPS 2023Beyond Normal: On the Evaluation of Mutual Information Estimators
41. NeurIPS 2023Building Socio-culturally Inclusive Stereotype Resources with Community Engagement
42. NeurIPS 2023Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
43. NeurIPS 2023Counterfactual Evaluation of Peer-Review Assignment Policies
44. NeurIPS 2023Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation
45. NeurIPS 2023CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews
46. NeurIPS 2023Curvature Filtrations for Graph Generative Model Evaluation
47. NeurIPS 2023FELM: Benchmarking Factuality Evaluation of Large Language Models
48. NeurIPS 2023Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
49. NeurIPS 2023Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment
50. NeurIPS 2023Optimal and Fair Encouragement Policy Evaluation and Learning

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · evaluation论文？

共 606 篇，按年份分别是 2023 年 53 篇、2024 年 115 篇、2025 年 208 篇、2026 年 230 篇。

NeurIPS 2026 有多少篇通用机器学习 · evaluation论文？

NeurIPS 2026 有 57 篇通用机器学习 · evaluation论文，上一届是 124 篇。

ICLR 2026 有多少篇通用机器学习 · evaluation论文？

ICLR 2026 有 19 篇通用机器学习 · evaluation论文，上一届是 19 篇。

ICML 2026 有多少篇通用机器学习 · evaluation论文？

ICML 2026 有 148 篇通用机器学习 · evaluation论文，上一届是 58 篇。

CVPR 2026 有多少篇通用机器学习 · evaluation论文？

CVPR 2026 有 6 篇通用机器学习 · evaluation论文，上一届是 7 篇。

哪个会议的通用机器学习 · evaluation论文最多？

NeurIPS，2023–2026 年共 270 篇。