社会层面 · accountability transparency and interpretability论文趋势 2023–2026

主要结论

• 社会层面 · accountability transparency and interpretability论文从 2023 年的 301 篇增长到 2026 年的 1,357 篇，三年间扩大到约 4.5 倍。
• NeurIPS 是发社会层面 · accountability transparency and interpretability论文最多的会议，2023–2026 年共 1,275 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是社会层面 · privacy：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 93 篇。
• 在「对齐与负责任 AI」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的社会层面 · safety是 93 倍，社会层面 · accountability transparency and interpretability是 4.5 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部社会层面 · accountability transparency and interpretability论文

共 522 篇，第 8 / 11 页

351. NeurIPS 2025Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry
352. NeurIPS 2025ProtoPairNet: Interpretable Regression through Prototypical Pair Reasoning
353. NeurIPS 2025Provable Gradient Editing of Deep Neural Networks
354. NeurIPS 2025Proxy-SPEX: Sample-Efficient Interpretability via Sparse Feature Interactions in LLMs
355. NeurIPS 2025Purifying Approximate Differential Privacy with Randomized Post-processing
356. NeurIPS 2025Quantifying Cross-Modality Memorization in Vision-Language Models
357. NeurIPS 2025Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
358. NeurIPS 2025Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2
359. NeurIPS 2025Reasoning Models Sometimes Output Illegible Chains of Thought
360. NeurIPS 2025Rectifying Shortcut Behaviors in Preference-based Reward Learning
361. NeurIPS 2025Redefining Experts: Interpretable Decomposition of Language Models for Toxicity Mitigation
362. NeurIPS 2025Regional Explanations: Bridging Local and Global Variable Importance
363. NeurIPS 2025Regression Trees Know Calculus
364. NeurIPS 2025Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
365. NeurIPS 2025Removing Concepts from Text-to-Image Models with Only Negative Samples
366. NeurIPS 2025Replicable Online pricing
367. NeurIPS 2025Representational Difference Explanations
368. NeurIPS 2025Rescaled Influence Functions: Accurate Data Attribution in High Dimension
369. NeurIPS 2025Residual Stream Analysis of Overfitting And Structural Disruptions
370. NeurIPS 2025Rethinking Circuit Completeness in Language Models: AND, OR, and ADDER Gates
371. NeurIPS 2025Rethinking Fair Federated Learning from Parameter and Client View
372. NeurIPS 2025Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
373. NeurIPS 2025Rethinking the Role of Verbatim Memorization in LLM Privacy
374. NeurIPS 2025Revising and Falsifying Sparse Autoencoder Feature Explanations
375. NeurIPS 2025Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability
376. NeurIPS 2025Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
377. NeurIPS 2025Ridge Boosting is Both Robust and Efficient
378. NeurIPS 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
379. NeurIPS 2025Robust and Scalable Autonomous Reinforcement Learning in Irreversible Environments
380. NeurIPS 2025Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
381. NeurIPS 2025Robust Explanations of Graph Neural Networks via Graph Curvatures
382. NeurIPS 2025Robust Integrated Learning and Pauli Noise Mitigation for Parametrized Quantum Circuits
383. NeurIPS 2025Robust SuperAlignment: Weak-to-Strong Robustness Generalization for Vision-Language Models
384. NeurIPS 2025RUAGO: Effective and Practical Retain-Free Unlearning via Adversarial Attack and OOD Generator
385. NeurIPS 2025SAEMark: Steering Personalized Multilingual LLM Watermarks with Sparse Autoencoders
386. NeurIPS 2025Safety Depth in Large Language Models: A Markov Chain Perspective
387. NeurIPS 2025SAFEx: Analyzing Vulnerabilities of MoE-Based LLMs via Stable Safety-critical Expert Identification
388. NeurIPS 2025Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
389. NeurIPS 2025Scalable Fingerprinting of Large Language Models
390. NeurIPS 2025Scalable Neural Network Geometric Robustness Validation via Hölder Optimisation
391. NeurIPS 2025Scalable Valuation of Human Feedback through Provably Robust Model Alignment
392. NeurIPS 2025SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations
393. NeurIPS 2025Second-Order Convergence in Private Stochastic Non-Convex Optimization
394. NeurIPS 2025Secure and Confidential Certificates of Online Fairness
395. NeurIPS 2025Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition
396. NeurIPS 2025Selective Omniprediction and Fair Abstention
397. NeurIPS 2025Semantic Representation Attack against Aligned Large Language Models
398. NeurIPS 2025Sequentially Auditing Differential Privacy
399. NeurIPS 2025SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
400. NeurIPS 2025SHAP values via sparse Fourier representation

常见问题

2023–2026 年四大会议一共有多少篇社会层面 · accountability transparency and interpretability论文？

共 3,411 篇，按年份分别是 2023 年 301 篇、2024 年 589 篇、2025 年 1,164 篇、2026 年 1,357 篇。

NeurIPS 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

NeurIPS 2026 有 416 篇社会层面 · accountability transparency and interpretability论文，上一届是 522 篇。

ICLR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

ICLR 2026 有 292 篇社会层面 · accountability transparency and interpretability论文，上一届是 211 篇。

ICML 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

ICML 2026 有 541 篇社会层面 · accountability transparency and interpretability论文，上一届是 337 篇。

CVPR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？

CVPR 2026 有 108 篇社会层面 · accountability transparency and interpretability论文，上一届是 94 篇。

哪个会议的社会层面 · accountability transparency and interpretability论文最多？

NeurIPS，2023–2026 年共 1,275 篇。