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

1,164 papers, page 11 of 24

501. ICML 2025Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
502. ICML 2025Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails
503. ICML 2025Not All Wrong is Bad: Using Adversarial Examples for Unlearning
504. ICML 2025Omni-Angle Assault: An Invisible and Powerful Physical Adversarial Attack on Face Recognition
505. ICML 2025On Explaining Equivariant Graph Networks via Improved Relevance Propagation
506. ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
507. ICML 2025On the Benefits of Active Data Collection in Operator Learning
508. ICML 2025On the Impact of Performative Risk Minimization for Binary Random Variables
509. ICML 2025On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
510. ICML 2025On the Private Estimation of Smooth Transport Maps
511. ICML 2025On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
512. ICML 2025One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
513. ICML 2025Optimal and Practical Batched Linear Bandit Algorithm
514. ICML 2025Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
515. ICML 2025Optimal Fair Learning Robust to Adversarial Distribution Shift
516. ICML 2025Optimizing Adaptive Attacks against Watermarks for Language Models
517. ICML 2025Optimizing Noise Distributions for Differential Privacy
518. ICML 2025Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
519. ICML 2025OR-Bench: An Over-Refusal Benchmark for Large Language Models
520. ICML 2025Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
521. ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
522. ICML 2025Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
523. ICML 2025Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
524. ICML 2025Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
525. ICML 2025Policy Design for Two-sided Platforms with Participation Dynamics
526. ICML 2025POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimization
527. ICML 2025Position: AI Agents Need Authenticated Delegation
528. ICML 2025Position: AI Safety should prioritize the Future of Work
529. ICML 2025Position: AI's growing due process problem
530. ICML 2025Position: Build Agent Advocates, Not Platform Agents
531. ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
532. ICML 2025Position: Contextual Integrity is Inadequately Applied to Language Models
533. ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
534. ICML 2025Position: Explainable AI Cannot Advance Without Better User Studies
535. ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
536. ICML 2025Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
537. ICML 2025Position: Language model developers should report train-test overlap
538. ICML 2025Position: Machine Learning Models Have a Supply Chain Problem
539. ICML 2025Position: Rethinking Explainable Machine Learning as Applied Statistics
540. ICML 2025Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
541. ICML 2025Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
542. ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
543. ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
544. ICML 2025Position: The Right to AI
545. ICML 2025Position: We Can’t Understand AI Using our Existing Vocabulary
546. ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation
547. ICML 2025Prediction via Shapley Value Regression
548. ICML 2025Prediction-Aware Learning in Multi-Agent Systems
549. ICML 2025Preference learning made easy: Everything should be understood through win rate
550. ICML 2025Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation

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.