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
83 papers, page 2 of 2
- ICLR 2024Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
- ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
- ICLR 2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
- ICLR 2024PRIME: Prioritizing Interpretability in Failure Mode Extraction
- ICLR 2024Quantifying the Plausibility of Context Reliance in Neural Machine Translation
- ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
- ICLR 2024Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
- ICLR 2024Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
- ICLR 2024Simplicial Representation Learning with Neural $k$-Forms
- ICLR 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
- ICLR 2024Social-Transmotion: Promptable Human Trajectory Prediction
- ICLR 2024Some Fundamental Aspects about Lipschitz Continuity of Neural Networks
- ICLR 2024SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
- ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
- ICLR 2024Stochastic Modified Equations and Dynamics of Dropout Algorithm
- ICLR 2024Subtractive Mixture Models via Squaring: Representation and Learning
- ICLR 2024Successor Heads: Recurring, Interpretable Attention Heads In The Wild
- ICLR 2024Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
- ICLR 2024The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
- ICLR 2024The Hidden Language of Diffusion Models
- ICLR 2024The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
- ICLR 2024The mechanistic basis of data dependence and abrupt learning in an in-context classification task
- ICLR 2024To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets
- ICLR 2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
- ICLR 2024Towards Transparent Time Series Forecasting
- ICLR 2024Towards Understanding Factual Knowledge of Large Language Models
- ICLR 2024Understanding Addition in Transformers
- ICLR 2024Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
- ICLR 2024Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
- ICLR 2024Unveiling and Manipulating Prompt Influence in Large Language Models
- ICLR 2024Vision Transformers Need Registers
- ICLR 2024What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity
- ICLR 2024What's In My Big Data?
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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.