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 1,124 篇，第 23 / 23 页

1101. ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
1102. ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
1103. ICML 2023Simple Disentanglement of Style and Content in Visual Representations
1104. ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
1105. ICML 2023Spurious Valleys and Clustering Behavior of Neural Networks
1106. ICML 2023Statistical Inference and A/B Testing for First-Price Pacing Equilibria
1107. ICML 2023Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation
1108. ICML 2023Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
1109. ICML 2023System Identification of Neural Systems: If We Got It Right, Would We Know?
1110. ICML 2023The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
1111. ICML 2023The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics
1112. ICML 2023The SSL Interplay: Augmentations, Inductive Bias, and Generalization
1113. ICML 2023Thompson Sampling with Less Exploration is Fast and Optimal
1114. ICML 2023Tight and fast generalization error bound of graph embedding in metric space
1115. ICML 2023Tilted Sparse Additive Models
1116. ICML 2023Towards a Persistence Diagram that is Robust to Noise and Varied Densities
1117. ICML 2023Towards Explaining Distribution Shifts
1118. ICML 2023Towards Reliable Neural Specifications
1119. ICML 2023Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
1120. ICML 2023Trainability, Expressivity and Interpretability in Gated Neural ODEs
1121. ICML 2023Uncertain Evidence in Probabilistic Models and Stochastic Simulators
1122. ICML 2023Understand and Modularize Generator Optimization in ELECTRA-style Pretraining
1123. ICML 2023Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
1124. ICML 2023When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

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。