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

416 papers, page 5 of 9

201. NeurIPS 2026Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values
202. NeurIPS 2026Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits
203. NeurIPS 2026LoRAcles: Self-Supervised Weight-Space Interpretability at Scale
204. NeurIPS 2026Loyalty Capture: Reporting Relationships and Structural Sycophancy in Frontier AI Models
205. NeurIPS 2026Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees
206. NeurIPS 2026Making Open-Source Text LLM Watermarks Durable Against Merging
207. NeurIPS 2026MarkTune: Improving the Quality-Detectability Trade-off in Model-Embedded LLM Watermarking
208. NeurIPS 2026Matryoshka Transcoders and Hierarchy Misalignment: When SAE Absorption Protection Does Not Transfer
209. NeurIPS 2026MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents
210. NeurIPS 2026Measuring and Strengthening Behavioral Suppression in Language Models
211. NeurIPS 2026Measuring Collapse and Correction in Homogeneous-Panel LLM Debate
212. NeurIPS 2026MedMisBench: Measuring Epistemic Resilience of LLMs Under Misleading Medical Context
213. NeurIPS 2026Memorization Is Folding: Topological Signatures of Noisy-Label Learning
214. NeurIPS 2026Memory Inception: Latent-Space KV Cache Manipulation for Steering LLMs
215. NeurIPS 2026MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents
216. NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
217. NeurIPS 2026Metaphor Is Not All Attention Needs
218. NeurIPS 2026Mitigating Memorization Where It Happens
219. NeurIPS 2026Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds
220. NeurIPS 2026Models Designed to Forget: Machine Unlearning via Key Deletion
221. NeurIPS 2026Models That Know How Evaluations Are Designed Score Safer
222. NeurIPS 2026Module Specialization in Transformer Factual Recall under Correlated Fact Distributions
223. NeurIPS 2026Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics
224. NeurIPS 2026MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents
225. NeurIPS 2026Multi-bit LLM Watermarking with Certified Semantic Distortion
226. NeurIPS 2026Multi-step Consistency Models: A Complete Error Theory and Optimal Step Selection
227. NeurIPS 2026Multilingual Safety Alignment via Self-Distillation
228. NeurIPS 2026Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again
229. NeurIPS 2026MultiSTEVE-1s: A Model Zoo and Interpretability Suite for Instruction-Following Vision Agents
230. NeurIPS 2026MUTE: Multi-Level Alignment Uncoupling Against Talking-Head Exploitation for Voice Protection
231. NeurIPS 2026Nash Social Welfare for Multi Armed Bandits: Trajectory-wise Expected and High Probability Regret
232. NeurIPS 2026Negation Neglect: When models fail to learn negations in training
233. NeurIPS 2026Nonparametric In-Context Learning under Growing Geometric Complexity: Minimax Optimality and Local Geometry-Adaptivity of Transformers
234. NeurIPS 2026Not all uncertainty is alike: volatility, stochasticity, and exploration
235. NeurIPS 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting
236. NeurIPS 2026On approximation and estimation of Schrödinger potentials without the curse of dimensionality
237. NeurIPS 2026On Differential Private $\ell_1$, $\ell_2$ and $\ell_p^p$ Distance Queries
238. NeurIPS 2026On Differentially Private Mechanisms for Linear Regression
239. NeurIPS 2026On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework
240. NeurIPS 2026On Nash Equilibria in Participatory Budgeting with Donations and Beyond
241. NeurIPS 2026On the Burden of Achieving Fairness in Conformal Prediction
242. NeurIPS 2026On the Depth of Monotone ReLU Neural Networks and ICNNs
243. NeurIPS 2026On the Meta-Design of Allocation Problems
244. NeurIPS 2026On the Tightness and Computational Tractability of Higher-Dimensional Confidence Sequences
245. NeurIPS 2026Online Differentially Private Consistent Clustering
246. NeurIPS 2026Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
247. NeurIPS 2026Online Set Learning from Precision and Recall Feedback
248. NeurIPS 2026Open-Ended Scientific Discovery and the Social Dynamics of Evolving Agent Networks
249. NeurIPS 2026OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations
250. NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy

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.