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 1,164 篇，第 21 / 24 页

1001. NeurIPS 2025Reasoning Models Sometimes Output Illegible Chains of Thought
1002. NeurIPS 2025Rectifying Shortcut Behaviors in Preference-based Reward Learning
1003. NeurIPS 2025Redefining Experts: Interpretable Decomposition of Language Models for Toxicity Mitigation
1004. NeurIPS 2025Regional Explanations: Bridging Local and Global Variable Importance
1005. NeurIPS 2025Regression Trees Know Calculus
1006. NeurIPS 2025Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
1007. NeurIPS 2025Removing Concepts from Text-to-Image Models with Only Negative Samples
1008. NeurIPS 2025Replicable Online pricing
1009. NeurIPS 2025Representational Difference Explanations
1010. NeurIPS 2025Rescaled Influence Functions: Accurate Data Attribution in High Dimension
1011. NeurIPS 2025Residual Stream Analysis of Overfitting And Structural Disruptions
1012. NeurIPS 2025Rethinking Circuit Completeness in Language Models: AND, OR, and ADDER Gates
1013. NeurIPS 2025Rethinking Fair Federated Learning from Parameter and Client View
1014. NeurIPS 2025Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
1015. NeurIPS 2025Rethinking the Role of Verbatim Memorization in LLM Privacy
1016. NeurIPS 2025Revising and Falsifying Sparse Autoencoder Feature Explanations
1017. NeurIPS 2025Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability
1018. NeurIPS 2025Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
1019. NeurIPS 2025Ridge Boosting is Both Robust and Efficient
1020. NeurIPS 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
1021. NeurIPS 2025Robust and Scalable Autonomous Reinforcement Learning in Irreversible Environments
1022. NeurIPS 2025Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
1023. NeurIPS 2025Robust Explanations of Graph Neural Networks via Graph Curvatures
1024. NeurIPS 2025Robust Integrated Learning and Pauli Noise Mitigation for Parametrized Quantum Circuits
1025. NeurIPS 2025Robust SuperAlignment: Weak-to-Strong Robustness Generalization for Vision-Language Models
1026. NeurIPS 2025RUAGO: Effective and Practical Retain-Free Unlearning via Adversarial Attack and OOD Generator
1027. NeurIPS 2025SAEMark: Steering Personalized Multilingual LLM Watermarks with Sparse Autoencoders
1028. NeurIPS 2025Safety Depth in Large Language Models: A Markov Chain Perspective
1029. NeurIPS 2025SAFEx: Analyzing Vulnerabilities of MoE-Based LLMs via Stable Safety-critical Expert Identification
1030. NeurIPS 2025Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
1031. NeurIPS 2025Scalable Fingerprinting of Large Language Models
1032. NeurIPS 2025Scalable Neural Network Geometric Robustness Validation via Hölder Optimisation
1033. NeurIPS 2025Scalable Valuation of Human Feedback through Provably Robust Model Alignment
1034. NeurIPS 2025SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations
1035. NeurIPS 2025Second-Order Convergence in Private Stochastic Non-Convex Optimization
1036. NeurIPS 2025Secure and Confidential Certificates of Online Fairness
1037. NeurIPS 2025Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition
1038. NeurIPS 2025Selective Omniprediction and Fair Abstention
1039. NeurIPS 2025Semantic Representation Attack against Aligned Large Language Models
1040. NeurIPS 2025Sequentially Auditing Differential Privacy
1041. NeurIPS 2025SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
1042. NeurIPS 2025SHAP values via sparse Fourier representation
1043. NeurIPS 2025SHAP zero Explains Biological Sequence Models with Near-zero Marginal Cost for Future Queries
1044. NeurIPS 2025Sharp Analysis for KL-Regularized Contextual Bandits and RLHF
1045. NeurIPS 2025Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
1046. NeurIPS 2025Shortcut Features as Top Eigenfunctions of NTK: A Linear Neural Network Case and More
1047. NeurIPS 2025Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
1048. NeurIPS 2025Simple and Effective Specialized Representations for Fair Classifiers
1049. NeurIPS 2025Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
1050. NeurIPS 2025SimWorld: An Open-ended Simulator for Agents in Physical and Social Worlds

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。