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 5 / 26 页
- NeurIPS 2026Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values
- NeurIPS 2026Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits
- NeurIPS 2026LoRAcles: Self-Supervised Weight-Space Interpretability at Scale
- NeurIPS 2026Loyalty Capture: Reporting Relationships and Structural Sycophancy in Frontier AI Models
- NeurIPS 2026Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees
- NeurIPS 2026Making Open-Source Text LLM Watermarks Durable Against Merging
- NeurIPS 2026MarkTune: Improving the Quality-Detectability Trade-off in Model-Embedded LLM Watermarking
- NeurIPS 2026Matryoshka Transcoders and Hierarchy Misalignment: When SAE Absorption Protection Does Not Transfer
- NeurIPS 2026MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents
- NeurIPS 2026Measuring and Strengthening Behavioral Suppression in Language Models
- NeurIPS 2026Measuring Collapse and Correction in Homogeneous-Panel LLM Debate
- NeurIPS 2026MedMisBench: Measuring Epistemic Resilience of LLMs Under Misleading Medical Context
- NeurIPS 2026Memorization Is Folding: Topological Signatures of Noisy-Label Learning
- NeurIPS 2026Memory Inception: Latent-Space KV Cache Manipulation for Steering LLMs
- NeurIPS 2026MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents
- NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
- NeurIPS 2026Metaphor Is Not All Attention Needs
- NeurIPS 2026Mitigating Memorization Where It Happens
- NeurIPS 2026Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds
- NeurIPS 2026Models Designed to Forget: Machine Unlearning via Key Deletion
- NeurIPS 2026Models That Know How Evaluations Are Designed Score Safer
- NeurIPS 2026Module Specialization in Transformer Factual Recall under Correlated Fact Distributions
- NeurIPS 2026Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics
- NeurIPS 2026MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents
- NeurIPS 2026Multi-bit LLM Watermarking with Certified Semantic Distortion
- NeurIPS 2026Multi-step Consistency Models: A Complete Error Theory and Optimal Step Selection
- NeurIPS 2026Multilingual Safety Alignment via Self-Distillation
- NeurIPS 2026Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again
- NeurIPS 2026MultiSTEVE-1s: A Model Zoo and Interpretability Suite for Instruction-Following Vision Agents
- NeurIPS 2026MUTE: Multi-Level Alignment Uncoupling Against Talking-Head Exploitation for Voice Protection
- NeurIPS 2026Nash Social Welfare for Multi Armed Bandits: Trajectory-wise Expected and High Probability Regret
- NeurIPS 2026Negation Neglect: When models fail to learn negations in training
- NeurIPS 2026Nonparametric In-Context Learning under Growing Geometric Complexity: Minimax Optimality and Local Geometry-Adaptivity of Transformers
- NeurIPS 2026Not all uncertainty is alike: volatility, stochasticity, and exploration
- NeurIPS 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting
- NeurIPS 2026On approximation and estimation of Schrödinger potentials without the curse of dimensionality
- NeurIPS 2026On Differential Private $\ell_1$, $\ell_2$ and $\ell_p^p$ Distance Queries
- NeurIPS 2026On Differentially Private Mechanisms for Linear Regression
- NeurIPS 2026On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework
- NeurIPS 2026On Nash Equilibria in Participatory Budgeting with Donations and Beyond
- NeurIPS 2026On the Burden of Achieving Fairness in Conformal Prediction
- NeurIPS 2026On the Depth of Monotone ReLU Neural Networks and ICNNs
- NeurIPS 2026On the Meta-Design of Allocation Problems
- NeurIPS 2026On the Tightness and Computational Tractability of Higher-Dimensional Confidence Sequences
- NeurIPS 2026Online Differentially Private Consistent Clustering
- NeurIPS 2026Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
- NeurIPS 2026Online Set Learning from Precision and Recall Feedback
- NeurIPS 2026Open-Ended Scientific Discovery and the Social Dynamics of Evolving Agent Networks
- NeurIPS 2026OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations
- NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy
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。