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

589 papers, page 7 of 12

301. ICML 2024Scaling Down Deep Learning with MNIST-1D
302. ICML 2024Scaling Exponents Across Parameterizations and Optimizers
303. ICML 2024Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
304. ICML 2024Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
305. ICML 2024SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
306. ICML 2024SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
307. ICML 2024Sparse and Structured Hopfield Networks
308. ICML 2024Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
309. ICML 2024Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
310. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
311. ICML 2024Stacking Deep Set Networks and Pooling by Quantiles
312. ICML 2024Symmetry Induces Structure and Constraint of Learning
313. ICML 2024The Emergence of Reproducibility and Consistency in Diffusion Models
314. ICML 2024The Entropy Enigma: Success and Failure of Entropy Minimization
315. ICML 2024The Good, The Bad, and Why: Unveiling Emotions in Generative AI
316. ICML 2024The Linear Representation Hypothesis and the Geometry of Large Language Models
317. ICML 2024Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
318. ICML 2024Topological Neural Networks go Persistent, Equivariant, and Continuous
319. ICML 2024Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
320. ICML 2024Towards Compositionality in Concept Learning
321. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
322. ICML 2024Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
323. ICML 2024Transformers, parallel computation, and logarithmic depth
324. ICML 2024Transforming and Combining Rewards for Aligning Large Language Models
325. ICML 2024Trustless Audits without Revealing Data or Models
326. ICML 2024Understanding and Diagnosing Deep Reinforcement Learning
327. ICML 2024Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
328. ICML 2024Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
329. ICML 2024Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
330. ICML 2024Verification of Machine Unlearning is Fragile
331. ICML 2024Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
332. ICML 2024Weighted distance nearest neighbor condensing
333. ICML 2024What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
334. ICML 2024When Representations Align: Universality in Representation Learning Dynamics
335. NeurIPS 20242D-OOB: Attributing Data Contribution Through Joint Valuation Framework
336. NeurIPS 20243-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
337. NeurIPS 2024A Concept-Based Explainability Framework for Large Multimodal Models
338. NeurIPS 2024A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
339. NeurIPS 2024A Functional Extension of Semi-Structured Networks
340. NeurIPS 2024A hierarchical decomposition for explaining ML performance discrepancies
341. NeurIPS 2024A Polar coordinate system represents syntax in large language models
342. NeurIPS 2024A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
343. NeurIPS 2024A Systematic Review of NeurIPS Dataset Management Practices
344. NeurIPS 2024A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
345. NeurIPS 2024A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
346. NeurIPS 2024Abrupt Learning in Transformers: A Case Study on Matrix Completion
347. NeurIPS 2024Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
348. NeurIPS 2024AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases
349. NeurIPS 2024Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP
350. NeurIPS 2024Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction

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.