社会层面 · accountability transparency and interpretability论文趋势 2023–2026

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。

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 1,124 篇，第 21 / 23 页

1001. ICML 2024SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
1002. ICML 2024SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
1003. ICML 2024Sparse and Structured Hopfield Networks
1004. ICML 2024Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
1005. ICML 2024Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
1006. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
1007. ICML 2024Stacking Deep Set Networks and Pooling by Quantiles
1008. ICML 2024Symmetry Induces Structure and Constraint of Learning
1009. ICML 2024The Emergence of Reproducibility and Consistency in Diffusion Models
1010. ICML 2024The Entropy Enigma: Success and Failure of Entropy Minimization
1011. ICML 2024The Good, The Bad, and Why: Unveiling Emotions in Generative AI
1012. ICML 2024The Linear Representation Hypothesis and the Geometry of Large Language Models
1013. ICML 2024Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
1014. ICML 2024Topological Neural Networks go Persistent, Equivariant, and Continuous
1015. ICML 2024Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
1016. ICML 2024Towards Compositionality in Concept Learning
1017. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
1018. ICML 2024Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
1019. ICML 2024Transformers, parallel computation, and logarithmic depth
1020. ICML 2024Transforming and Combining Rewards for Aligning Large Language Models
1021. ICML 2024Trustless Audits without Revealing Data or Models
1022. ICML 2024Understanding and Diagnosing Deep Reinforcement Learning
1023. ICML 2024Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
1024. ICML 2024Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
1025. ICML 2024Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
1026. ICML 2024Verification of Machine Unlearning is Fragile
1027. ICML 2024Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
1028. ICML 2024Weighted distance nearest neighbor condensing
1029. ICML 2024What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
1030. ICML 2024When Representations Align: Universality in Representation Learning Dynamics
1031. ICML 2023A Closer Look at the Intervention Procedure of Concept Bottleneck Models
1032. ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
1033. ICML 2023A Law of Robustness beyond Isoperimetry
1034. ICML 2023A Modern Look at the Relationship between Sharpness and Generalization
1035. ICML 2023A Study on Transformer Configuration and Training Objective
1036. ICML 2023A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations
1037. ICML 2023abess: A Fast Best-Subset Selection Library in Python and R
1038. ICML 2023AdaBoost is not an Optimal Weak to Strong Learner
1039. ICML 2023Adaptive Coordination in Social Embodied Rearrangement
1040. ICML 2023Adversarial Classification: Necessary Conditions and Geometric Flows
1041. ICML 2023Are Equivariant Equilibrium Approximators Beneficial?
1042. ICML 2023Bandit Online Linear Optimization with Hints and Queries
1043. ICML 2023Bandits with Knapsacks: Advice on Time-Varying Demands
1044. ICML 2023Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts
1045. ICML 2023Better Training of GFlowNets with Local Credit and Incomplete Trajectories
1046. ICML 2023Bootstrap in High Dimension with Low Computation
1047. ICML 2023Brauer's Group Equivariant Neural Networks
1048. ICML 2023Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
1049. ICML 2023Consistency of Multiple Kernel Clustering
1050. ICML 2023Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets

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。