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 589 篇，第 7 / 12 页

301. ICML 2024Scaling Down Deep Learning with MNIST-1D
302. ICML 2024Scaling Exponents Across Parameterizations and Optimizers
303. ICML 2024Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
304. ICML 2024Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
305. ICML 2024SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
306. ICML 2024SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
307. ICML 2024Sparse and Structured Hopfield Networks
308. ICML 2024Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
309. ICML 2024Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
310. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
311. ICML 2024Stacking Deep Set Networks and Pooling by Quantiles
312. ICML 2024Symmetry Induces Structure and Constraint of Learning
313. ICML 2024The Emergence of Reproducibility and Consistency in Diffusion Models
314. ICML 2024The Entropy Enigma: Success and Failure of Entropy Minimization
315. ICML 2024The Good, The Bad, and Why: Unveiling Emotions in Generative AI
316. ICML 2024The Linear Representation Hypothesis and the Geometry of Large Language Models
317. ICML 2024Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
318. ICML 2024Topological Neural Networks go Persistent, Equivariant, and Continuous
319. ICML 2024Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
320. ICML 2024Towards Compositionality in Concept Learning
321. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
322. ICML 2024Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
323. ICML 2024Transformers, parallel computation, and logarithmic depth
324. ICML 2024Transforming and Combining Rewards for Aligning Large Language Models
325. ICML 2024Trustless Audits without Revealing Data or Models
326. ICML 2024Understanding and Diagnosing Deep Reinforcement Learning
327. ICML 2024Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
328. ICML 2024Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
329. ICML 2024Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
330. ICML 2024Verification of Machine Unlearning is Fragile
331. ICML 2024Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
332. ICML 2024Weighted distance nearest neighbor condensing
333. ICML 2024What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
334. ICML 2024When Representations Align: Universality in Representation Learning Dynamics
335. NeurIPS 20242D-OOB: Attributing Data Contribution Through Joint Valuation Framework
336. NeurIPS 20243-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
337. NeurIPS 2024A Concept-Based Explainability Framework for Large Multimodal Models
338. NeurIPS 2024A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
339. NeurIPS 2024A Functional Extension of Semi-Structured Networks
340. NeurIPS 2024A hierarchical decomposition for explaining ML performance discrepancies
341. NeurIPS 2024A Polar coordinate system represents syntax in large language models
342. NeurIPS 2024A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
343. NeurIPS 2024A Systematic Review of NeurIPS Dataset Management Practices
344. NeurIPS 2024A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
345. NeurIPS 2024A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
346. NeurIPS 2024Abrupt Learning in Transformers: A Case Study on Matrix Completion
347. NeurIPS 2024Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
348. NeurIPS 2024AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases
349. NeurIPS 2024Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP
350. NeurIPS 2024Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction

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。