社会层面 · accountability transparency and interpretability论文趋势 2023–2026

主要结论

• 社会层面 · accountability transparency and interpretability论文从 2023 年的 301 篇增长到 2026 年的 1,357 篇，三年间扩大到约 4.5 倍。
• NeurIPS 是发社会层面 · accountability transparency and interpretability论文最多的会议，2023–2026 年共 1,275 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是社会层面 · privacy：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 93 篇。
• 在「对齐与负责任 AI」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的社会层面 · safety是 93 倍，社会层面 · accountability transparency and interpretability是 4.5 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 2026A Unifying Perspective on Language Model Interpretability
• ICML 2026$\texttt{PRISM}$:A 3D Probabilistic Neural Representation for Interpretable Shape Modeling
• ICLR 2026Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers
• CVPR 2026Beyond Matching to Tiles Bridging Unaligned Aerial and Satellite Views
• NeurIPS 2025$\mathcal{X}^2$-DFD: A framework for e$\mathcal{X}$plainable and e$\mathcal{X}$tendable Deepfake Detection
• ICML 2025(How) Can Transformers Predict Pseudo-Random Numbers?
• ICLR 2025Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
• CVPR 2025Attribute-formed Class-specific Concept Space: Endowing Language Bottleneck Model with Better Interpretability and Scalability
• NeurIPS 20242D-OOB: Attributing Data Contribution Through Joint Valuation Framework
• ICML 2024Attention Meets Post-hoc Interpretability: A Mathematical Perspective
• ICLR 2024"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
• CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
• NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
• ICML 2023A Modern Look at the Relationship between Sharpness and Generalization
• ICLR 2023Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization
• CVPR 2023Analyzing and Diagnosing Pose Estimation With Attributions
• NeurIPS 2026AdKnob: Ad Intensity Control and Labeling for LLM-Native Advertising
• ICML 2026$\texttt{ShaplEIG}$: Bayesian Experimental Design for Shapley Value Estimation
• ICLR 2026Bandits with Single-Peaked Preferences and Limited Resources
• CVPR 2026IEBGLAn Interpretability-Enhanced Brain Graph Learning Framework with LLM-Instructed Topology and

全部社会层面 · accountability transparency and interpretability论文

共 152 篇，第 2 / 4 页

51. ICML 2024Grokking Group Multiplication with Cosets
52. ICML 2024High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
53. ICML 2024High-Performance Temporal Reversible Spiking Neural Networks with $\mathcal{O}(L)$ Training Memory and $\mathcal{O}(1)$ Inference Cost
54. ICML 2024How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
55. ICML 2024How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
56. ICML 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
57. ICML 2024Imitation Learning from Purified Demonstrations
58. ICML 2024Improving Neural Additive Models with Bayesian Principles
59. ICML 2024Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining
60. ICML 2024InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
61. ICML 2024Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
62. ICML 2024Interpretability Illusions in the Generalization of Simplified Models
63. ICML 2024Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
64. ICML 2024Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
65. ICML 2024KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations
66. ICML 2024Language Models Represent Beliefs of Self and Others
67. ICML 2024Large Language Models are Geographically Biased
68. ICML 2024LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
69. ICML 2024Learning and Forgetting Unsafe Examples in Large Language Models
70. ICML 2024Learning to Intervene on Concept Bottlenecks
71. ICML 2024Light and Optimal Schrödinger Bridge Matching
72. ICML 2024LLaGA: Large Language and Graph Assistant
73. ICML 2024Local vs. Global Interpretability: A Computational Complexity Perspective
74. ICML 2024Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
75. ICML 2024MGit: A Model Versioning and Management System
76. ICML 2024Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
77. ICML 2024Model Assessment and Selection under Temporal Distribution Shift
78. ICML 2024MultiMax: Sparse and Multi-Modal Attention Learning
79. ICML 2024Naive Bayes Classifiers over Missing Data: Decision and Poisoning
80. ICML 2024NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction
81. ICML 2024Observable Propagation: Uncovering Feature Vectors in Transformers
82. ICML 2024Offline Training of Language Model Agents with Functions as Learnable Weights
83. ICML 2024On a Combinatorial Problem Arising in Machine Teaching
84. ICML 2024On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning
85. ICML 2024On the Implicit Bias of Adam
86. ICML 2024Optimally Improving Cooperative Learning in a Social Setting
87. ICML 2024Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors
88. ICML 2024Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
89. ICML 2024OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
90. ICML 2024Partial Optimality in the Linear Ordering Problem
91. ICML 2024Performative Prediction with Bandit Feedback: Learning through Reparameterization
92. ICML 2024Perturb-and-Project: Differentially Private Similarities and Marginals
93. ICML 2024Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach
94. ICML 2024PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
95. ICML 2024Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research
96. ICML 2024Position: AI/ML Influencers Have a Place in the Academic Process
97. ICML 2024Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
98. ICML 2024Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis
99. ICML 2024Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
100. ICML 2024Position: Evolving AI Collectives Enhance Human Diversity and Enable Self-Regulation

常见问题

2023–2026 年四大会议一共有多少篇社会层面 · accountability transparency and interpretability论文？

共 3,411 篇，按年份分别是 2023 年 301 篇、2024 年 589 篇、2025 年 1,164 篇、2026 年 1,357 篇。

NeurIPS 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

NeurIPS 2026 有 416 篇社会层面 · accountability transparency and interpretability论文，上一届是 522 篇。

ICLR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

ICLR 2026 有 292 篇社会层面 · accountability transparency and interpretability论文，上一届是 211 篇。

ICML 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

ICML 2026 有 541 篇社会层面 · accountability transparency and interpretability论文，上一届是 337 篇。

CVPR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

CVPR 2026 有 108 篇社会层面 · accountability transparency and interpretability论文，上一届是 94 篇。

哪个会议的社会层面 · accountability transparency and interpretability论文最多？

NeurIPS，2023–2026 年共 1,275 篇。