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

3,411 papers, page 24 of 69

1151. NeurIPS 2026Measuring and Strengthening Behavioral Suppression in Language Models
1152. NeurIPS 2026Measuring Collapse and Correction in Homogeneous-Panel LLM Debate
1153. NeurIPS 2026MedMisBench: Measuring Epistemic Resilience of LLMs Under Misleading Medical Context
1154. NeurIPS 2026Memorization Is Folding: Topological Signatures of Noisy-Label Learning
1155. NeurIPS 2026Memory Inception: Latent-Space KV Cache Manipulation for Steering LLMs
1156. NeurIPS 2026MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents
1157. NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
1158. NeurIPS 2026Metaphor Is Not All Attention Needs
1159. NeurIPS 2026Mitigating Memorization Where It Happens
1160. NeurIPS 2026Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds
1161. NeurIPS 2026Models Designed to Forget: Machine Unlearning via Key Deletion
1162. NeurIPS 2026Models That Know How Evaluations Are Designed Score Safer
1163. NeurIPS 2026Module Specialization in Transformer Factual Recall under Correlated Fact Distributions
1164. NeurIPS 2026Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics
1165. NeurIPS 2026MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents
1166. NeurIPS 2026Multi-bit LLM Watermarking with Certified Semantic Distortion
1167. NeurIPS 2026Multi-step Consistency Models: A Complete Error Theory and Optimal Step Selection
1168. NeurIPS 2026Multilingual Safety Alignment via Self-Distillation
1169. NeurIPS 2026Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again
1170. NeurIPS 2026MultiSTEVE-1s: A Model Zoo and Interpretability Suite for Instruction-Following Vision Agents
1171. NeurIPS 2026MUTE: Multi-Level Alignment Uncoupling Against Talking-Head Exploitation for Voice Protection
1172. NeurIPS 2026Nash Social Welfare for Multi Armed Bandits: Trajectory-wise Expected and High Probability Regret
1173. NeurIPS 2026Negation Neglect: When models fail to learn negations in training
1174. NeurIPS 2026Nonparametric In-Context Learning under Growing Geometric Complexity: Minimax Optimality and Local Geometry-Adaptivity of Transformers
1175. NeurIPS 2026Not all uncertainty is alike: volatility, stochasticity, and exploration
1176. NeurIPS 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting
1177. NeurIPS 2026On approximation and estimation of Schrödinger potentials without the curse of dimensionality
1178. NeurIPS 2026On Differential Private $\ell_1$, $\ell_2$ and $\ell_p^p$ Distance Queries
1179. NeurIPS 2026On Differentially Private Mechanisms for Linear Regression
1180. NeurIPS 2026On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework
1181. NeurIPS 2026On Nash Equilibria in Participatory Budgeting with Donations and Beyond
1182. NeurIPS 2026On the Burden of Achieving Fairness in Conformal Prediction
1183. NeurIPS 2026On the Depth of Monotone ReLU Neural Networks and ICNNs
1184. NeurIPS 2026On the Meta-Design of Allocation Problems
1185. NeurIPS 2026On the Tightness and Computational Tractability of Higher-Dimensional Confidence Sequences
1186. NeurIPS 2026Online Differentially Private Consistent Clustering
1187. NeurIPS 2026Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
1188. NeurIPS 2026Online Set Learning from Precision and Recall Feedback
1189. NeurIPS 2026Open-Ended Scientific Discovery and the Social Dynamics of Evolving Agent Networks
1190. NeurIPS 2026OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations
1191. NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy
1192. NeurIPS 2026Optimal Rates for Adaptive Private $k$-PCA
1193. NeurIPS 2026Optimal Rates for Differentially Private Hypothesis Testing with E-values
1194. NeurIPS 2026Optimistic Dual Averaging Unifies Modern Optimizers
1195. NeurIPS 2026Optimizer-Induced Mode Connectivity: From AdamW to Muon
1196. NeurIPS 2026Optimizing Social Utility in Sequential Experiments
1197. NeurIPS 2026Outbidding and Outbluffing Elite Humans: Mastering Liar’s Poker via Self-Play and Reinforcement Learning
1198. NeurIPS 2026PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
1199. NeurIPS 2026Parasite Features: Causal Abstraction Through Spurious Pathways
1200. NeurIPS 2026Participatory ML for Social Harm Should be Constructed, Validated and Reasoned Through First-Person Accounts

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.