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 25 / 69 页
- NeurIPS 2026PatchBench: Measuring Collateral Damage in Activation Patching
- NeurIPS 2026Pause and Reflect: Conformal Aggregation for Chain-of-Thought Reasoning
- NeurIPS 2026PDHFormer: Progressive Dual-Head Transformer for Behavioral Choice Prediction
- NeurIPS 2026Per-Starting-Point Plausibility and Diversity Bounds for Score-Based Diffusion Models
- NeurIPS 2026Persona Vectors: Monitoring and Controlling Character Traits in Language Models
- NeurIPS 2026Persona-Model Collapse in Emergent Misalignment
- NeurIPS 2026Plug-and-Play ADMM for Inverse Problems with Flow Matching Denoiser
- NeurIPS 2026Pose-Free Feed-Forward 3D Inpainting via Learnable Mask Attention and Support Token Refinement
- NeurIPS 2026Position-aware eXplanation: A Model-Agnostic Framework for Positional Attributions
- NeurIPS 2026Position: Life-Logging Video Streams Make the Privacy–Utility Trade-off Inevitable
- NeurIPS 2026Position: Machine Learning Conferences Should Introduce an Autonomous Research Track
- NeurIPS 2026Position: Reconciling Open Access with Owner Control in AI Model Distribution Deserves More Research Effort
- NeurIPS 2026Position: We Need Greater Transparency to Maintain Research Pipeline Reliability Despite GenAI
- NeurIPS 2026Positional Encoding and Prompt-Order Sensitivity in In-Context Learning
- NeurIPS 2026PP-Mark: Provable and Publicly Verifiable Watermarking for Generative AI
- NeurIPS 2026Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels
- NeurIPS 2026Prediction-Intervention Games and Invariant Sets
- NeurIPS 2026Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants
- NeurIPS 2026Prevailing Bisimulation Metric Learning Is Biased: Implicit Regularization and Its Remedy
- NeurIPS 2026PRISM: Polarimetric Road-surface Intelligent Sensing and Measurement Dataset
- NeurIPS 2026Privacy Amplification Persists under Unlimited Synthetic Data Release
- NeurIPS 2026Privacy Risk Scales with Effective Dimension in Federated Learning
- NeurIPS 2026PrivacySIM: Evaluating LLM Simulation of User Privacy Behavior
- NeurIPS 2026Private Online Prediction from Experts with Small Losses
- NeurIPS 2026PrivateSeal: Low-Sensitivity Latent Directions for Diffusion-Resilient User-Specific Watermarking
- NeurIPS 2026PROACT-Agent: Progressive Runtime Oversight and Active Circuit-breaking for Real-Time Safety
- NeurIPS 2026ProjKAN: Model Compression via KAN Projections to Bridge the Hypothesis and Capacity Gaps
- NeurIPS 2026Prompts to Proxies: Emulating Human Preferences via a Compact LLM Ensemble
- NeurIPS 2026Provable Explanations for Any-Order Neural Additive Models
- NeurIPS 2026Proxy-Based Approximation of Shapley and Banzhaf Interactions
- NeurIPS 2026quanda: An Interpretability Toolkit for Training Data Attribution Evaluation
- NeurIPS 2026Rank-Constrained Adaptation for Reliable Real-World Performance
- NeurIPS 2026Reaching a Consensus in Predictive Loops
- NeurIPS 2026Reading the Finetuning Prior: Verbatim Content Recovery via Contrastive Decoding Diffing
- NeurIPS 2026Recursively Trained Diffusion Models: Limiting Collapse Distribution and Spectral Characterization
- NeurIPS 2026Register Anything Model for Generalizable and Robust Point Cloud Registration
- NeurIPS 2026Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
- NeurIPS 2026Rep2Text: Decoding Full Text from a Single LLM Token Representation
- NeurIPS 2026Representation Rigidity in Face Embeddings: Orthogonal Identifiability and Backfill-Free Compatibility
- NeurIPS 2026Response Time Enhances Alignment with Heterogeneous Preferences
- NeurIPS 2026Retain-Neutral Surrogates for Min-Max Unlearning
- NeurIPS 2026Rethinking Sequential Locate-Then-Edit: Optimality and Stability
- NeurIPS 2026Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings
- NeurIPS 2026Revealing the Gap in Human and VLM Scene Perception through Counterfactual Semantic Saliency
- NeurIPS 2026Revisiting Incremental Learning: A Three-Interface Diagnosis of Stability and Plasticity
- NeurIPS 2026Revisiting Subgradient Dominance in Robust MDPs: Counterexamples, Hardness, and Sufficient Conditions
- NeurIPS 2026Revisiting Value Iteration: Unified Analysis of Discounted and Average-Reward Cases
- NeurIPS 2026Risks Create a Jagged Frontier of LLM Productivity Gains Across Computer Occupations
- NeurIPS 2026Robust and Efficient Continual Model Merging via Global Singular Subspace Separation and Restoration
- NeurIPS 2026Robust and Scalable Collaborative Learning via Pull-Based Epidemic Communication
在 Claude、Cursor 里直接问这个趋势
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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。