社会层面 · accountability transparency and interpretability论文趋势 2023–2026
AI 社会议题：accountability_transparency_and_interpretability
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 3,411 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 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 |
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 3,411 篇，第 67 / 69 页
- ICML 2023Robust and private stochastic linear bandits
- ICML 2023Robust and Scalable Bayesian Online Changepoint Detection
- ICML 2023Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
- ICML 2023Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
- ICML 2023Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm.
- ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
- ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
- ICML 2023Simple Disentanglement of Style and Content in Visual Representations
- ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
- ICML 2023Spurious Valleys and Clustering Behavior of Neural Networks
- ICML 2023Statistical Inference and A/B Testing for First-Price Pacing Equilibria
- ICML 2023Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation
- ICML 2023Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
- ICML 2023System Identification of Neural Systems: If We Got It Right, Would We Know?
- ICML 2023The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
- ICML 2023The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics
- ICML 2023The SSL Interplay: Augmentations, Inductive Bias, and Generalization
- ICML 2023Thompson Sampling with Less Exploration is Fast and Optimal
- ICML 2023Tight and fast generalization error bound of graph embedding in metric space
- ICML 2023Tilted Sparse Additive Models
- ICML 2023Towards a Persistence Diagram that is Robust to Noise and Varied Densities
- ICML 2023Towards Explaining Distribution Shifts
- ICML 2023Towards Reliable Neural Specifications
- ICML 2023Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
- ICML 2023Trainability, Expressivity and Interpretability in Gated Neural ODEs
- ICML 2023Uncertain Evidence in Probabilistic Models and Stochastic Simulators
- ICML 2023Understand and Modularize Generator Optimization in ELECTRA-style Pretraining
- ICML 2023Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
- ICML 2023When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
- NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
- NeurIPS 2023[Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods
- NeurIPS 2023[Re] VAE Approximation Error: ELBO and Exponential Families
- NeurIPS 2023A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
- NeurIPS 2023A normative theory of social conflict
- NeurIPS 2023A Robust and Opponent-Aware League Training Method for StarCraft II
- NeurIPS 2023Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
- NeurIPS 2023Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
- NeurIPS 2023Auxiliary Losses for Learning Generalizable Concept-based Models
- NeurIPS 2023BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing
- NeurIPS 2023Bridging Discrete and Backpropagation: Straight-Through and Beyond
- NeurIPS 2023Core-sets for Fair and Diverse Data Summarization
- NeurIPS 2023D-Separation for Causal Self-Explanation
- NeurIPS 2023D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
- NeurIPS 2023DISCOVER: Making Vision Networks Interpretable via Competition and Dissection
- NeurIPS 2023Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability
- NeurIPS 2023Disentangling Cognitive Diagnosis with Limited Exercise Labels
- NeurIPS 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
- NeurIPS 2023Double Auctions with Two-sided Bandit Feedback
- NeurIPS 2023Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
- NeurIPS 2023Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查社会层面 · accountability transparency and interpretability在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "social-accountability-transparency-and-interpretability"}
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。