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
337 papers, page 5 of 7
- ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
- ICML 2025On the Benefits of Active Data Collection in Operator Learning
- ICML 2025On the Impact of Performative Risk Minimization for Binary Random Variables
- ICML 2025On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
- ICML 2025On the Private Estimation of Smooth Transport Maps
- ICML 2025On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
- ICML 2025One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
- ICML 2025Optimal and Practical Batched Linear Bandit Algorithm
- ICML 2025Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
- ICML 2025Optimal Fair Learning Robust to Adversarial Distribution Shift
- ICML 2025Optimizing Adaptive Attacks against Watermarks for Language Models
- ICML 2025Optimizing Noise Distributions for Differential Privacy
- ICML 2025Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
- ICML 2025OR-Bench: An Over-Refusal Benchmark for Large Language Models
- ICML 2025Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
- ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
- ICML 2025Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
- ICML 2025Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
- ICML 2025Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
- ICML 2025Policy Design for Two-sided Platforms with Participation Dynamics
- ICML 2025POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimization
- ICML 2025Position: AI Agents Need Authenticated Delegation
- ICML 2025Position: AI Safety should prioritize the Future of Work
- ICML 2025Position: AI's growing due process problem
- ICML 2025Position: Build Agent Advocates, Not Platform Agents
- ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
- ICML 2025Position: Contextual Integrity is Inadequately Applied to Language Models
- ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
- ICML 2025Position: Explainable AI Cannot Advance Without Better User Studies
- ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
- ICML 2025Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
- ICML 2025Position: Language model developers should report train-test overlap
- ICML 2025Position: Machine Learning Models Have a Supply Chain Problem
- ICML 2025Position: Rethinking Explainable Machine Learning as Applied Statistics
- ICML 2025Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
- ICML 2025Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
- ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
- ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
- ICML 2025Position: The Right to AI
- ICML 2025Position: We Can’t Understand AI Using our Existing Vocabulary
- ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation
- ICML 2025Prediction via Shapley Value Regression
- ICML 2025Prediction-Aware Learning in Multi-Agent Systems
- ICML 2025Preference learning made easy: Everything should be understood through win rate
- ICML 2025Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
- ICML 2025Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty
- ICML 2025Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
- ICML 2025Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
- ICML 2025Quantifying Memory Utilization with Effective State-Size
- ICML 2025Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
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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.