Social aspects · accountability transparency and interpretability papers, 2023–2026

Key findings

• Social aspects · accountability transparency and interpretability went from 301 papers in 2023 to 1,357 in 2026, roughly 4.5x in three years.
• NeurIPS publishes the most Social aspects · accountability transparency and interpretability work: 1,275 papers from 2023 to 2026, 37% of the four-venue total.
• The fastest-growing overlap is with Social aspects · privacy: papers tagged with both rose from 0 in 2023 to 93 in 2026.
• Among the 5 topics under Alignment and Responsible AI, it ranks #2 by 2026 paper count; the fastest grower in the group, Social aspects · safety, is up 93x versus 4.5x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Social aspects · accountability transparency and interpretability papers

94 papers, page 2 of 2

51. ICML 2023On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
52. ICML 2023On Preemption and Learning in Stochastic Scheduling
53. ICML 2023On Regularization and Inference with Label Constraints
54. ICML 2023On the Functional Similarity of Robust and Non-Robust Neural Representations
55. ICML 2023On the Impact of Algorithmic Recourse on Social Segregation
56. ICML 2023On the Impact of Knowledge Distillation for Model Interpretability
57. ICML 2023On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
58. ICML 2023On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
59. ICML 2023Optimal Sets and Solution Paths of ReLU Networks
60. ICML 2023Polarity Is All You Need to Learn and Transfer Faster
61. ICML 2023Project and Forget: Solving Large-Scale Metric Constrained Problems
62. ICML 2023Pruning via Sparsity-indexed ODE: a Continuous Sparsity Viewpoint
63. ICML 2023Quantifying Human Priors over Social and Navigation Networks
64. ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
65. ICML 2023Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
66. ICML 2023Robust and private stochastic linear bandits
67. ICML 2023Robust and Scalable Bayesian Online Changepoint Detection
68. ICML 2023Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
69. ICML 2023Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
70. ICML 2023Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm.
71. ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
72. ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
73. ICML 2023Simple Disentanglement of Style and Content in Visual Representations
74. ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
75. ICML 2023Spurious Valleys and Clustering Behavior of Neural Networks
76. ICML 2023Statistical Inference and A/B Testing for First-Price Pacing Equilibria
77. ICML 2023Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation
78. ICML 2023Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
79. ICML 2023System Identification of Neural Systems: If We Got It Right, Would We Know?
80. ICML 2023The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
81. ICML 2023The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics
82. ICML 2023The SSL Interplay: Augmentations, Inductive Bias, and Generalization
83. ICML 2023Thompson Sampling with Less Exploration is Fast and Optimal
84. ICML 2023Tight and fast generalization error bound of graph embedding in metric space
85. ICML 2023Tilted Sparse Additive Models
86. ICML 2023Towards a Persistence Diagram that is Robust to Noise and Varied Densities
87. ICML 2023Towards Explaining Distribution Shifts
88. ICML 2023Towards Reliable Neural Specifications
89. ICML 2023Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
90. ICML 2023Trainability, Expressivity and Interpretability in Gated Neural ODEs
91. ICML 2023Uncertain Evidence in Probabilistic Models and Stochastic Simulators
92. ICML 2023Understand and Modularize Generator Optimization in ELECTRA-style Pretraining
93. ICML 2023Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
94. ICML 2023When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

FAQ

How many Social aspects · accountability transparency and interpretability papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

3,411 in total: 301 in 2023, 589 in 2024, 1,164 in 2025, 1,357 in 2026.

How many Social aspects · accountability transparency and interpretability papers are at NeurIPS 2026?

NeurIPS 2026 has 416 Social aspects · accountability transparency and interpretability papers, versus 522 the year before.

How many Social aspects · accountability transparency and interpretability papers are at ICLR 2026?

ICLR 2026 has 292 Social aspects · accountability transparency and interpretability papers, versus 211 the year before.

How many Social aspects · accountability transparency and interpretability papers are at ICML 2026?

ICML 2026 has 541 Social aspects · accountability transparency and interpretability papers, versus 337 the year before.

How many Social aspects · accountability transparency and interpretability papers are at CVPR 2026?

CVPR 2026 has 108 Social aspects · accountability transparency and interpretability papers, versus 94 the year before.

Which conference publishes the most Social aspects · accountability transparency and interpretability papers?

NeurIPS, with 1,275 papers from 2023 to 2026.