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

301 papers, page 4 of 7

151. ICML 2023Explainability as statistical inference
152. ICML 2023Fair and Accurate Decision Making through Group-Aware Learning
153. ICML 2023Fast Excess Risk Rates via Offset Rademacher Complexity
154. ICML 2023Feature learning in deep classifiers through Intermediate Neural Collapse
155. ICML 2023Finding Generalization Measures by Contrasting Signal and Noise
156. ICML 2023Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds
157. ICML 2023Gibbsian Polar Slice Sampling
158. ICML 2023Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond
159. ICML 2023Graph Neural Networks with Learnable and Optimal Polynomial Bases
160. ICML 2023Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing
161. ICML 2023Hierarchies of Reward Machines
162. ICML 2023High-dimensional Clustering onto Hamiltonian Cycle
163. ICML 2023How to address monotonicity for model risk management?
164. ICML 2023Incentivizing Exploration with Linear Contexts and Combinatorial Actions
165. ICML 2023Investigating the Role of Model-Based Learning in Exploration and Transfer
166. ICML 2023Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation
167. ICML 2023Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
168. ICML 2023Learning Mixtures of Markov Chains and MDPs
169. ICML 2023Learning Prescriptive ReLU Networks
170. ICML 2023Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning
171. ICML 2023Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
172. ICML 2023LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
173. ICML 2023MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
174. ICML 2023Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals
175. ICML 2023On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization
176. ICML 2023On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
177. ICML 2023On Preemption and Learning in Stochastic Scheduling
178. ICML 2023On Regularization and Inference with Label Constraints
179. ICML 2023On the Functional Similarity of Robust and Non-Robust Neural Representations
180. ICML 2023On the Impact of Algorithmic Recourse on Social Segregation
181. ICML 2023On the Impact of Knowledge Distillation for Model Interpretability
182. ICML 2023On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
183. ICML 2023On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
184. ICML 2023Optimal Sets and Solution Paths of ReLU Networks
185. ICML 2023Polarity Is All You Need to Learn and Transfer Faster
186. ICML 2023Project and Forget: Solving Large-Scale Metric Constrained Problems
187. ICML 2023Pruning via Sparsity-indexed ODE: a Continuous Sparsity Viewpoint
188. ICML 2023Quantifying Human Priors over Social and Navigation Networks
189. ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
190. ICML 2023Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
191. ICML 2023Robust and private stochastic linear bandits
192. ICML 2023Robust and Scalable Bayesian Online Changepoint Detection
193. ICML 2023Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
194. ICML 2023Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
195. ICML 2023Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm.
196. ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
197. ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
198. ICML 2023Simple Disentanglement of Style and Content in Visual Representations
199. ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
200. ICML 2023Spurious Valleys and Clustering Behavior of Neural Networks

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.