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 1,275 篇，第 24 / 26 页
- NeurIPS 2024Testing Semantic Importance via Betting
- NeurIPS 2024The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
- NeurIPS 2024The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More
- NeurIPS 2024The Intelligible and Effective Graph Neural Additive Network
- NeurIPS 2024The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
- NeurIPS 2024The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models
- NeurIPS 2024The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track
- NeurIPS 2024The Surprising Effectiveness of SP Voting with Partial Preferences
- NeurIPS 2024The tree autoencoder model, with application to hierarchical data visualization
- NeurIPS 2024Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks
- NeurIPS 2024Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox
- NeurIPS 2024Towards Neuron Attributions in Multi-Modal Large Language Models
- NeurIPS 2024Towards Scalable and Stable Parallelization of Nonlinear RNNs
- NeurIPS 2024Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens
- NeurIPS 2024Trading off Consistency and Dimensionality of Convex Surrogates for Multiclass Classification
- NeurIPS 2024Training Data Attribution via Approximate Unrolling
- NeurIPS 2024Training for Stable Explanation for Free
- NeurIPS 2024Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^\pi$-Realizability and Concentrability
- NeurIPS 2024Transcoders find interpretable LLM feature circuits
- NeurIPS 2024Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization
- NeurIPS 2024Transformer Doctor: Diagnosing and Treating Vision Transformers
- NeurIPS 2024Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
- NeurIPS 2024Transformers on Markov data: Constant depth suffices
- NeurIPS 2024Transformers Represent Belief State Geometry in their Residual Stream
- NeurIPS 2024Truth is Universal: Robust Detection of Lies in LLMs
- NeurIPS 2024Understanding and Minimising Outlier Features in Transformer Training
- NeurIPS 2024Understanding Information Storage and Transfer in Multi-Modal Large Language Models
- NeurIPS 2024Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective
- NeurIPS 2024Understanding Transformers via N-Gram Statistics
- NeurIPS 2024Understanding Visual Feature Reliance through the Lens of Complexity
- NeurIPS 2024Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback
- NeurIPS 2024Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
- NeurIPS 2024Using Noise to Infer Aspects of Simplicity Without Learning
- NeurIPS 2024VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance
- NeurIPS 2024What Makes and Breaks Safety Fine-tuning? A Mechanistic Study
- NeurIPS 2024What makes unlearning hard and what to do about it
- NeurIPS 2024What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information
- NeurIPS 2024When is an Embedding Model More Promising than Another?
- NeurIPS 2024Where does In-context Learning Happen in Large Language Models?
- NeurIPS 2024Who's asking? User personas and the mechanics of latent misalignment
- NeurIPS 2024Why are Visually-Grounded Language Models Bad at Image Classification?
- NeurIPS 2024Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training
- NeurIPS 2024Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference
- 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
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。