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 606 篇，第 1 / 13 页

1. CVPR 2026Bridging the Perception Gap in Image Super-Resolution Evaluation
2. CVPR 2026CrossHOI-Bench A Unified Benchmark for HOI Evaluation across Vision-Language Models
3. CVPR 2026Focal-General Diffusion Model with Semantic Consistent Guidance for Sign Language
4. CVPR 2026SpatialScore Towards Comprehensive Evaluation for Spatial Intelligence
5. CVPR 2026Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks
6. CVPR 2026UI-Lens Assessing General MLLMs Potential to Automate UI Display Quality
7. ICLR 2026A General Framework for Black-Box Attacks Under Cost Asymmetry
8. ICLR 2026A Relative Error-Based Evaluation Framework of Heterogeneous Treatment Effect Estimators
9. ICLR 2026Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP Solvers
10. ICLR 2026Choices Speak Louder than Questions
11. ICLR 2026Conformalized Survival Counterfactuals Prediction for General Right-Censored Data
12. ICLR 2026DUET: Optimizing LLM Training Data Mixtures via Noisy Feedback from Unseen, Downstream Evaluation Tasks
13. ICLR 2026Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation
14. ICLR 2026Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation
15. ICLR 2026Internal Evaluation of Density-Based Clusterings with Noise
16. ICLR 2026LFQA-E: Carefully Benchmarking Long-form QA Evaluation
17. ICLR 2026Multiple-Prediction-Powered Inference
18. ICLR 2026Off-Policy Evaluation for Ranking Policies under Deterministic Logging Policies
19. ICLR 2026Predicting Training Re-evaluation Curves Enables Effective Data Curriculums for LLMs
20. ICLR 2026Quantum machine learning advantages beyond hardness of evaluation
21. ICLR 2026Rectified Decoupled Dataset Distillation: A Closer Look for Fair and Comprehensive Evaluation
22. ICLR 2026Rethinking LLM Evaluation: Can We Evaluate LLMs with 200× Less Data?
23. ICLR 2026SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding
24. ICLR 2026The Lie of the Average: How Class Incremental Learning Evaluation Deceives You?
25. ICLR 2026Unlearning Evaluation through Subset Statistical Independence
26. ICML 2026A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
27. ICML 2026A Computational Framework for Evaluating Human-likeness in LLMs' Open-ended Human Behaviors
28. ICML 2026A Diagnostic Study of Multi-Agent LLMs for Real-World Debates
29. ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
30. ICML 2026A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems
31. ICML 2026Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative
32. ICML 2026Accurate Evaluation of Quickest Changepoint Detectors via Non-parametric Survival Analysis
33. ICML 2026Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks
34. ICML 2026AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition
35. ICML 2026AgentSuite: Toward More Reliable Agent Evaluation with a Component-Based Benchmark Auditing Pipeline
36. ICML 2026AI Cartography: Mapping the Latent Landscape of AI Benchmark Ecosystems
37. ICML 2026Anytime-Valid Inference for Online Ranking of Large Language Models
38. ICML 2026Approximation Preserving Coresets
39. ICML 2026Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination
40. ICML 2026Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints
41. ICML 2026AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
42. ICML 2026Attention Sinks in Diffusion Transformers: A Causal Analysis
43. ICML 2026BEDTime: A Unified Benchmark for Automatically Describing Time Series
44. ICML 2026Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks
45. ICML 2026Benchmarking at the Edge of Comprehension
46. ICML 2026Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis
47. ICML 2026Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
48. ICML 2026Benchmarking World-Model Learning with Environment-Level Queries
49. ICML 2026BEST: Benchmarking Efficiency in Space and Time for LLM-Generated Code
50. ICML 2026Beyond Benchmarks: Toward Causally Faithful Evaluation of Large Language Models

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。