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

643 papers, page 12 of 13

551. ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
552. ICLR 2024On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
553. ICLR 2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
554. ICLR 2024Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
555. ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
556. ICLR 2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
557. ICLR 2024PRIME: Prioritizing Interpretability in Failure Mode Extraction
558. ICLR 2024Quantifying the Plausibility of Context Reliance in Neural Machine Translation
559. ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
560. ICLR 2024Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
561. ICLR 2024Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
562. ICLR 2024Simplicial Representation Learning with Neural $k$-Forms
563. ICLR 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
564. ICLR 2024Social-Transmotion: Promptable Human Trajectory Prediction
565. ICLR 2024Some Fundamental Aspects about Lipschitz Continuity of Neural Networks
566. ICLR 2024SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
567. ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
568. ICLR 2024Stochastic Modified Equations and Dynamics of Dropout Algorithm
569. ICLR 2024Subtractive Mixture Models via Squaring: Representation and Learning
570. ICLR 2024Successor Heads: Recurring, Interpretable Attention Heads In The Wild
571. ICLR 2024Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
572. ICLR 2024The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
573. ICLR 2024The Hidden Language of Diffusion Models
574. ICLR 2024The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
575. ICLR 2024The mechanistic basis of data dependence and abrupt learning in an in-context classification task
576. ICLR 2024To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets
577. ICLR 2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
578. ICLR 2024Towards Transparent Time Series Forecasting
579. ICLR 2024Towards Understanding Factual Knowledge of Large Language Models
580. ICLR 2024Understanding Addition in Transformers
581. ICLR 2024Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
582. ICLR 2024Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
583. ICLR 2024Unveiling and Manipulating Prompt Influence in Large Language Models
584. ICLR 2024Vision Transformers Need Registers
585. ICLR 2024What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity
586. ICLR 2024What's In My Big Data?
587. ICLR 2023A Differential Geometric View and Explainability of GNN on Evolving Graphs
588. ICLR 2023A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond
589. ICLR 2023A law of adversarial risk, interpolation, and label noise
590. ICLR 2023A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
591. ICLR 2023Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
592. ICLR 2023Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks
593. ICLR 2023Avoiding spurious correlations via logit correction
594. ICLR 2023Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
595. ICLR 2023Compositional Law Parsing with Latent Random Functions
596. ICLR 2023Concept Gradient: Concept-based Interpretation Without Linear Assumption
597. ICLR 2023Continuous-time identification of dynamic state-space models by deep subspace encoding
598. ICLR 2023DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
599. ICLR 2023DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
600. ICLR 2023Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization

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.