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
1,357 papers, page 14 of 28
- ICML 2026How Language Models Process Negation
- ICML 2026How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs
- ICML 2026Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
- ICML 2026HumanLM: Simulating Users with State Alignment Beats Response Imitation
- ICML 2026HyperPotter: Spell the Charm of High-Order Interactions in Audio Deepfake Detection
- ICML 2026IACW: Intent-Aware Controllable Watermarking for Scalable Authorial Intent Attribution
- ICML 2026Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction
- ICML 2026Improved Algorithms for Nash Welfare in Linear Bandits
- ICML 2026Improved Bounds for Private and Robust Alignment
- ICML 2026Improving Adversarial Robustness of Attribution via Implicit Regularization
- ICML 2026In-Context Universal Approximation, Compositional Generalization, and Algorithm Emulation
- ICML 2026In-Training Defenses Against Emergent Misalignment in Language Models
- ICML 2026Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
- ICML 2026Induction Meets Biology: Mechanisms of Repeat Detection in Protein Language Models
- ICML 2026Instance-Specific Approximation Ratios for Correlation Clustering and Max-Cut
- ICML 2026Interpretability and Generalization Bounds for Learning Spatial Physics
- ICML 2026Interpretability Driven Evolutionary Approach for the Design of Biological Sequences
- ICML 2026Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
- ICML 2026Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation
- ICML 2026Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow
- ICML 2026Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks
- ICML 2026Interpreting Genomic Language Models using Sparse Autoencoders
- ICML 2026Introspection Adapters: Training LLMs to Report Their Learned Behaviors
- ICML 2026IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
- ICML 2026Is Data Shapley Not Better than Random in Data Selection? Ask NASH
- ICML 2026Is Your LLM Overcharging You? Tokenization, Transparency, and Incentives
- ICML 2026IVQ: Structured and Lightweight Vector Quantization via Binary Hierarchical Composition Inspired by $\textit{IChing}$
- ICML 2026Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
- ICML 2026Jailbreak to Protect: Buffering and Reinforcing via Temporary Jailbreaking for Safe Fine-Tuning in Large Language Models
- ICML 2026Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
- ICML 2026Language as a Wave Phenomenon: Semantic Phase Locking and Interference in Neural Networks
- ICML 2026Language Model Circuits Are Sparse in the Neuron Basis
- ICML 2026LAPRAS : Learning-Augmented PRivate Answering for linear query Streams.
- ICML 2026Large Language Models Develop Novel Social Biases Through Adaptive Exploration
- ICML 2026LatentLens: Revealing Highly Interpretable Visual Tokens in LLMs
- ICML 2026Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs
- ICML 2026Learning a Generative Meta-Model of LLM Activations
- ICML 2026Learning Coherent Representations: A Topological Approach to Interpretability
- ICML 2026Learning Efficient Guardrails for Compliance
- ICML 2026Learning Junta Distributions, Quantum Junta States, and QAC$^0$ Circuits
- ICML 2026Learning Manifold Data with Flow Matching
- ICML 2026Learning to Remember, Learn, and Forget in Attention-Based Models
- ICML 2026Learning to Watermark in the Latent Space of Generative Models
- ICML 2026Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs
- ICML 2026LLM Self-Recognition: Steering and Retrieving Activation Signatures
- ICML 2026LMCleaner: Efficient and Certified Online Unlearning via Influence Propagation Truncation
- ICML 2026Localize and Neutralize: Gradient-Guided Token Suppression Against Visual Prompt Injection Attack
- ICML 2026Locate then Correct: Debiasing Attention Heads in CLIP
- ICML 2026Long-term Fairness with Selective Labels
- ICML 2026Low-Compute Watermark Removal via Dual-Domain Natural Projection
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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.