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 1 of 2
- ICLR 2024"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
- ICLR 2024A Benchmark Study on Calibration
- ICLR 2024A path-norm toolkit for modern networks: consequences, promises and challenges
- ICLR 2024A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
- ICLR 2024AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
- ICLR 2024Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
- ICLR 2024Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
- ICLR 2024Benchmarking and Improving Generator-Validator Consistency of Language Models
- ICLR 2024Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
- ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
- ICLR 2024Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks
- ICLR 2024CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis
- ICLR 2024Circuit Component Reuse Across Tasks in Transformer Language Models
- ICLR 2024Compositional Preference Models for Aligning LMs
- ICLR 2024CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
- ICLR 2024Demystifying Embedding Spaces using Large Language Models
- ICLR 2024Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
- ICLR 2024Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
- ICLR 2024Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
- ICLR 2024Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations
- ICLR 2024EX-Graph: A Pioneering Dataset Bridging Ethereum and X
- ICLR 2024Explaining Kernel Clustering via Decision Trees
- ICLR 2024Exploring the cloud of feature interaction scores in a Rashomon set
- ICLR 2024Faithful Vision-Language Interpretation via Concept Bottleneck Models
- ICLR 2024Faster Approximation of Probabilistic and Distributional Values via Least Squares
- ICLR 2024FedImpro: Measuring and Improving Client Update in Federated Learning
- ICLR 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
- ICLR 2024Function Vectors in Large Language Models
- ICLR 2024GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
- ICLR 2024GOAt: Explaining Graph Neural Networks via Graph Output Attribution
- ICLR 2024How do Language Models Bind Entities in Context?
- ICLR 2024Improving Convergence and Generalization Using Parameter Symmetries
- ICLR 2024In-Context Learning Dynamics with Random Binary Sequences
- ICLR 2024Inherently Interpretable Time Series Classification via Multiple Instance Learning
- ICLR 2024Interpreting CLIP's Image Representation via Text-Based Decomposition
- ICLR 2024Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching
- ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
- ICLR 2024Language Models Represent Space and Time
- ICLR 2024Linearity of Relation Decoding in Transformer Language Models
- ICLR 2024Masks, Signs, And Learning Rate Rewinding
- ICLR 2024Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
- ICLR 2024Meta-Learning Priors Using Unrolled Proximal Networks
- ICLR 2024More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
- ICLR 2024Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace
- ICLR 2024Non-negative Contrastive Learning
- ICLR 2024On Double Descent in Reinforcement Learning with LSTD and Random Features
- ICLR 2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
- ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
- ICLR 2024On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
- ICLR 2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
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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.