Social aspects · accountability transparency and interpretability papers, 2023–2026
Social aspect: accountability_transparency_and_interpretability
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 3,411 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 82 | 57 | 94 | 68 | 301 |
| 2024 | 255 | 83 | 152 | 99 | 589 |
| 2025 | 522 | 211 | 337 | 94 | 1,164 |
| 2026 | 416 | 292 | 541 | 108 | 1,357 |
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 66 of 69
- ICML 2023Bootstrap in High Dimension with Low Computation
- ICML 2023Brauer's Group Equivariant Neural Networks
- ICML 2023Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
- ICML 2023Consistency of Multiple Kernel Clustering
- ICML 2023Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets
- ICML 2023Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
- ICML 2023Curriculum Co-disentangled Representation Learning across Multiple Environments for Social Recommendation
- ICML 2023Discover and Cure: Concept-aware Mitigation of Spurious Correlation
- ICML 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark
- ICML 2023Expected Gradients of Maxout Networks and Consequences to Parameter Initialization
- ICML 2023Explainability as statistical inference
- ICML 2023Fair and Accurate Decision Making through Group-Aware Learning
- ICML 2023Fast Excess Risk Rates via Offset Rademacher Complexity
- ICML 2023Feature learning in deep classifiers through Intermediate Neural Collapse
- ICML 2023Finding Generalization Measures by Contrasting Signal and Noise
- ICML 2023Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds
- ICML 2023Gibbsian Polar Slice Sampling
- ICML 2023Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond
- ICML 2023Graph Neural Networks with Learnable and Optimal Polynomial Bases
- ICML 2023Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing
- ICML 2023Hierarchies of Reward Machines
- ICML 2023High-dimensional Clustering onto Hamiltonian Cycle
- ICML 2023How to address monotonicity for model risk management?
- ICML 2023Incentivizing Exploration with Linear Contexts and Combinatorial Actions
- ICML 2023Investigating the Role of Model-Based Learning in Exploration and Transfer
- ICML 2023Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation
- ICML 2023Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
- ICML 2023Learning Mixtures of Markov Chains and MDPs
- ICML 2023Learning Prescriptive ReLU Networks
- ICML 2023Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning
- ICML 2023Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
- ICML 2023LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
- ICML 2023MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
- ICML 2023Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals
- ICML 2023On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization
- ICML 2023On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
- ICML 2023On Preemption and Learning in Stochastic Scheduling
- ICML 2023On Regularization and Inference with Label Constraints
- ICML 2023On the Functional Similarity of Robust and Non-Robust Neural Representations
- ICML 2023On the Impact of Algorithmic Recourse on Social Segregation
- ICML 2023On the Impact of Knowledge Distillation for Model Interpretability
- ICML 2023On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
- ICML 2023On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
- ICML 2023Optimal Sets and Solution Paths of ReLU Networks
- ICML 2023Polarity Is All You Need to Learn and Transfer Faster
- ICML 2023Project and Forget: Solving Large-Scale Metric Constrained Problems
- ICML 2023Pruning via Sparsity-indexed ODE: a Continuous Sparsity Viewpoint
- ICML 2023Quantifying Human Priors over Social and Navigation Networks
- ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
- ICML 2023Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
Ask about this trend from Claude or Cursor
Connect the Paperlist MCP and your assistant can pull the numbers on this page while you draft a survey, pick a direction or plan a submission: papers per year and venue, growth, the fastest-rising sub-themes and representative papers, shaped around your question.
Copy this prompt into your assistant
Use paperlist to show how Social aspects · accountability transparency and interpretability papers grew at NeurIPS from 2023 to 2026, and which year jumped the most.
Tool the assistant calls: get_topic_stats {"topic": "social-accountability-transparency-and-interpretability"}
Set up Paperlist MCP in two minutes (Claude Code, Cursor, Codex, ChatGPT)
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.