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 83 篇，第 1 / 2 页

1. ICLR 2024"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
2. ICLR 2024A Benchmark Study on Calibration
3. ICLR 2024A path-norm toolkit for modern networks: consequences, promises and challenges
4. ICLR 2024A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
5. ICLR 2024AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
6. ICLR 2024Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
7. ICLR 2024Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
8. ICLR 2024Benchmarking and Improving Generator-Validator Consistency of Language Models
9. ICLR 2024Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
10. ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
11. ICLR 2024Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks
12. ICLR 2024CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis
13. ICLR 2024Circuit Component Reuse Across Tasks in Transformer Language Models
14. ICLR 2024Compositional Preference Models for Aligning LMs
15. ICLR 2024CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
16. ICLR 2024Demystifying Embedding Spaces using Large Language Models
17. ICLR 2024Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
18. ICLR 2024Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
19. ICLR 2024Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
20. ICLR 2024Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations
21. ICLR 2024EX-Graph: A Pioneering Dataset Bridging Ethereum and X
22. ICLR 2024Explaining Kernel Clustering via Decision Trees
23. ICLR 2024Exploring the cloud of feature interaction scores in a Rashomon set
24. ICLR 2024Faithful Vision-Language Interpretation via Concept Bottleneck Models
25. ICLR 2024Faster Approximation of Probabilistic and Distributional Values via Least Squares
26. ICLR 2024FedImpro: Measuring and Improving Client Update in Federated Learning
27. ICLR 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
28. ICLR 2024Function Vectors in Large Language Models
29. ICLR 2024GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
30. ICLR 2024GOAt: Explaining Graph Neural Networks via Graph Output Attribution
31. ICLR 2024How do Language Models Bind Entities in Context?
32. ICLR 2024Improving Convergence and Generalization Using Parameter Symmetries
33. ICLR 2024In-Context Learning Dynamics with Random Binary Sequences
34. ICLR 2024Inherently Interpretable Time Series Classification via Multiple Instance Learning
35. ICLR 2024Interpreting CLIP's Image Representation via Text-Based Decomposition
36. ICLR 2024Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching
37. ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
38. ICLR 2024Language Models Represent Space and Time
39. ICLR 2024Linearity of Relation Decoding in Transformer Language Models
40. ICLR 2024Masks, Signs, And Learning Rate Rewinding
41. ICLR 2024Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
42. ICLR 2024Meta-Learning Priors Using Unrolled Proximal Networks
43. ICLR 2024More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
44. ICLR 2024Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace
45. ICLR 2024Non-negative Contrastive Learning
46. ICLR 2024On Double Descent in Reinforcement Learning with LSTD and Random Features
47. ICLR 2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
48. ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
49. ICLR 2024On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
50. ICLR 2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks

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。