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

1,275 papers, page 11 of 26

501. NeurIPS 2025Consensus-Robust Transfer Attacks via Parameter and Representation Perturbations
502. NeurIPS 2025Contextual Integrity in LLMs via Reasoning and Reinforcement Learning
503. NeurIPS 2025Contimask: Explaining Irregular Time Series via Perturbations in Continuous Time
504. NeurIPS 2025Continual Release Moment Estimation with Differential Privacy
505. NeurIPS 2025Continuity and Isolation Lead to Doubts or Dilemmas in Large Language Models
506. NeurIPS 2025Continuous Concepts Removal in Text-to-image Diffusion Models
507. NeurIPS 2025Controlling The Spread of Epidemics on Networks with Differential Privacy
508. NeurIPS 2025Controlling Thinking Speed in Reasoning Models
509. NeurIPS 2025Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning
510. NeurIPS 2025CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
511. NeurIPS 2025CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment
512. NeurIPS 2025Correcting misinterpretations of additive models
513. NeurIPS 2025Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
514. NeurIPS 2025Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training
515. NeurIPS 2025Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models
516. NeurIPS 2025CryptoMoE: Privacy-Preserving and Scalable Mixture of Experts Inference via Balanced Expert Routing
517. NeurIPS 2025CTRL-ALT-DECEIT Sabotage Evaluations for Automated AI R&D
518. NeurIPS 2025CVGL: Causal Learning and Geometric Topology
519. NeurIPS 2025Data-Free Model Extraction for Black-box Recommender Systems via Graph Convolutions
520. NeurIPS 2025Deep Learning with Plausible Deniability
521. NeurIPS 2025Deep Value Benchmark: Measuring Whether Models Generalize Deep values or Shallow Preferences
522. NeurIPS 2025Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
523. NeurIPS 2025Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
524. NeurIPS 2025DEGauss: Defending Against Malicious 3D Editing for Gaussian Splatting
525. NeurIPS 2025Dense SAE Latents Are Features, Not Bugs
526. NeurIPS 2025DePass: Unified Feature Attributing by Simple Decomposed Forward Pass
527. NeurIPS 2025DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
528. NeurIPS 2025Detecting Generated Images by Fitting Natural Image Distributions
529. NeurIPS 2025Detecting High-Stakes Interactions with Activation Probes
530. NeurIPS 2025Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing
531. NeurIPS 2025DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control
532. NeurIPS 2025DictPFL: Efficient and Private Federated Learning on Encrypted Gradients
533. NeurIPS 2025DiffBreak: Is Diffusion-Based Purification Robust?
534. NeurIPS 2025Differentiable Sparsity via $D$-Gating: Simple and Versatile Structured Penalization
535. NeurIPS 2025Differential Privacy on Fully Dynamic Streams
536. NeurIPS 2025Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
537. NeurIPS 2025Differentially Private Gomory-Hu Trees
538. NeurIPS 2025Differentially Private High-dimensional Variable Selection via Integer Programming
539. NeurIPS 2025Differentially Private Quantiles with Smaller Error
540. NeurIPS 2025Differentially Private Relational Learning with Entity-level Privacy Guarantees
541. NeurIPS 2025Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive
542. NeurIPS 2025Dimensionality Mismatch Between Brains and Artificial Neural Networks
543. NeurIPS 2025Direct Alignment with Heterogeneous Preferences
544. NeurIPS 2025Discovering Opinion Intervals from Conflicts in Signed Graphs
545. NeurIPS 2025Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
546. NeurIPS 2025Disentangling Superpositions: Interpretable Brain Encoding Model with Sparse Concept Atoms
547. NeurIPS 2025Distillation Robustifies Unlearning
548. NeurIPS 2025DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
549. NeurIPS 2025Do different prompting methods yield a common task representation in language models?
550. NeurIPS 2025Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness

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.