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 643 篇，第 12 / 13 页

551. ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
552. ICLR 2024On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
553. ICLR 2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
554. ICLR 2024Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
555. ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
556. ICLR 2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
557. ICLR 2024PRIME: Prioritizing Interpretability in Failure Mode Extraction
558. ICLR 2024Quantifying the Plausibility of Context Reliance in Neural Machine Translation
559. ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
560. ICLR 2024Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
561. ICLR 2024Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
562. ICLR 2024Simplicial Representation Learning with Neural $k$-Forms
563. ICLR 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
564. ICLR 2024Social-Transmotion: Promptable Human Trajectory Prediction
565. ICLR 2024Some Fundamental Aspects about Lipschitz Continuity of Neural Networks
566. ICLR 2024SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
567. ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
568. ICLR 2024Stochastic Modified Equations and Dynamics of Dropout Algorithm
569. ICLR 2024Subtractive Mixture Models via Squaring: Representation and Learning
570. ICLR 2024Successor Heads: Recurring, Interpretable Attention Heads In The Wild
571. ICLR 2024Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
572. ICLR 2024The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
573. ICLR 2024The Hidden Language of Diffusion Models
574. ICLR 2024The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
575. ICLR 2024The mechanistic basis of data dependence and abrupt learning in an in-context classification task
576. ICLR 2024To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets
577. ICLR 2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
578. ICLR 2024Towards Transparent Time Series Forecasting
579. ICLR 2024Towards Understanding Factual Knowledge of Large Language Models
580. ICLR 2024Understanding Addition in Transformers
581. ICLR 2024Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
582. ICLR 2024Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
583. ICLR 2024Unveiling and Manipulating Prompt Influence in Large Language Models
584. ICLR 2024Vision Transformers Need Registers
585. ICLR 2024What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity
586. ICLR 2024What's In My Big Data?
587. ICLR 2023A Differential Geometric View and Explainability of GNN on Evolving Graphs
588. ICLR 2023A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond
589. ICLR 2023A law of adversarial risk, interpolation, and label noise
590. ICLR 2023A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
591. ICLR 2023Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
592. ICLR 2023Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks
593. ICLR 2023Avoiding spurious correlations via logit correction
594. ICLR 2023Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
595. ICLR 2023Compositional Law Parsing with Latent Random Functions
596. ICLR 2023Concept Gradient: Concept-based Interpretation Without Linear Assumption
597. ICLR 2023Continuous-time identification of dynamic state-space models by deep subspace encoding
598. ICLR 2023DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
599. ICLR 2023DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
600. ICLR 2023Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization

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。