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 2 / 13 页

51. ICML 2026Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
52. ICML 2026Causally Evaluating the Learnability of Formal Language Tasks
53. ICML 2026CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
54. ICML 2026CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
55. ICML 2026Certifying Capabilities from Finite Tests: When Is It Possible?
56. ICML 2026CHB: A Diagnostic Toolkit for Hardness-Aware Clustering Evaluation
57. ICML 2026CIRBench: Evaluating Large Language Models as LLVM IR Optimizers
58. ICML 2026CiteGuard: Conformal False-Discovery Control for Faithful Retrieval-Augmented Generation
59. ICML 2026Clustered Influence Functions
60. ICML 2026CodeClash: Benchmarking Goal-Oriented Software Engineering
61. ICML 2026Conditional Coverage Diagnostics for Conformal Prediction
62. ICML 2026Conformal Reliability: A New Evaluation Metric for Conditional Generation
63. ICML 2026Contrastive Order Learning: A General Framework for Ordinal Regression
64. ICML 2026Correct Looks Better: Pairwise Comparisons Reveal Accuracy Rankings
65. ICML 2026Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation
66. ICML 2026Cutting LLM Evaluation Costs with SySRs: A Bandit Algorithm That Provably Exploits Model Similarity
67. ICML 2026CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities
68. ICML 2026DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation
69. ICML 2026Divisiveness-Consistent Label Distribution Learning
70. ICML 2026DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model
71. ICML 2026Do LLMs Signal When They’re Right? Evidence from Neuron Agreement
72. ICML 2026Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs
73. ICML 2026DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents
74. ICML 2026DRIFT-BENCH: Diagnosing CoopeRative Breakdowns in LLM Agents under Input Faults via Multi-Turn Interaction
75. ICML 2026DRPBench: Evaluating LLMs in Concurrent Code Comprehension via Fine-Grained Data Race Prediction
76. ICML 2026DSGym: A Standardized and Holistic Framework for Evaluating and Training Data Science Agents
77. ICML 2026Dynamic High-Dimensional Facility Location with Low Recourse
78. ICML 2026Efficient Inference for Noisy LLM-as-a-Judge Evaluation
79. ICML 2026Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
80. ICML 2026Estimating Correlation Clustering Cost in Node-Arrival Stream
81. ICML 2026Estimating the Empowerment of Language Model Agents
82. ICML 2026Evaluating Language Models in Realistic Conversational Contexts
83. ICML 2026Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
84. ICML 2026Evaluating Object-Centric Models beyond Object Discovery
85. ICML 2026Evaluating Robustness of Reasoning Models on Parameterized Logical Problems
86. ICML 2026EVMbench: Evaluating AI Agents on Smart Contract Security
87. ICML 2026EvoClaw: Evaluating AI Agents on Continuous Software Evolution
88. ICML 2026Expanding the AI Evaluation Toolbox with Statistical Models
89. ICML 2026Explainable Federated Learning via Global–Local Attribution Alignment
90. ICML 2026Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
91. ICML 2026FiRE: Fine-grained Ranking Evaluation for Machine Translation
92. ICML 2026Fix Before Search: Benchmarking Agentic Visual Query Pre-processing in Multimodal Retrieval-augmented Generation
93. ICML 2026FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences
94. ICML 2026FormalRx: Rectify and eXamine Semantic Failures in Autoformalization
95. ICML 2026FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
96. ICML 2026GameDevBench: Evaluating Agentic Capabilities Through Game Development
97. ICML 2026General Analysis of LMO-based Optimizers: Beyond Bounded Variance
98. ICML 2026GenExam: A Multidisciplinary Text-to-Image Exam
99. ICML 2026GICDM: Mitigating Hubness for Reliable Distance-Based Generative Model Evaluation
100. ICML 2026How can we assess human-agent interactions? Case studies in software agent design

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。