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 337 篇，第 5 / 7 页
- ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
- ICML 2025On the Benefits of Active Data Collection in Operator Learning
- ICML 2025On the Impact of Performative Risk Minimization for Binary Random Variables
- ICML 2025On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
- ICML 2025On the Private Estimation of Smooth Transport Maps
- ICML 2025On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
- ICML 2025One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
- ICML 2025Optimal and Practical Batched Linear Bandit Algorithm
- ICML 2025Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
- ICML 2025Optimal Fair Learning Robust to Adversarial Distribution Shift
- ICML 2025Optimizing Adaptive Attacks against Watermarks for Language Models
- ICML 2025Optimizing Noise Distributions for Differential Privacy
- ICML 2025Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
- ICML 2025OR-Bench: An Over-Refusal Benchmark for Large Language Models
- ICML 2025Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
- ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
- ICML 2025Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
- ICML 2025Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
- ICML 2025Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
- ICML 2025Policy Design for Two-sided Platforms with Participation Dynamics
- ICML 2025POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimization
- ICML 2025Position: AI Agents Need Authenticated Delegation
- ICML 2025Position: AI Safety should prioritize the Future of Work
- ICML 2025Position: AI's growing due process problem
- ICML 2025Position: Build Agent Advocates, Not Platform Agents
- ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
- ICML 2025Position: Contextual Integrity is Inadequately Applied to Language Models
- ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
- ICML 2025Position: Explainable AI Cannot Advance Without Better User Studies
- ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
- ICML 2025Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
- ICML 2025Position: Language model developers should report train-test overlap
- ICML 2025Position: Machine Learning Models Have a Supply Chain Problem
- ICML 2025Position: Rethinking Explainable Machine Learning as Applied Statistics
- ICML 2025Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
- ICML 2025Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
- ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
- ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
- ICML 2025Position: The Right to AI
- ICML 2025Position: We Can’t Understand AI Using our Existing Vocabulary
- ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation
- ICML 2025Prediction via Shapley Value Regression
- ICML 2025Prediction-Aware Learning in Multi-Agent Systems
- ICML 2025Preference learning made easy: Everything should be understood through win rate
- ICML 2025Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
- ICML 2025Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty
- ICML 2025Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
- ICML 2025Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
- ICML 2025Quantifying Memory Utilization with Effective State-Size
- ICML 2025Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
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。