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 3,411 篇，第 60 / 69 页

2951. NeurIPS 2024Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models
2952. NeurIPS 2024Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing
2953. NeurIPS 2024Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models
2954. NeurIPS 2024Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion
2955. NeurIPS 2024InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques
2956. NeurIPS 2024Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
2957. NeurIPS 2024Interpretable Concept-Based Memory Reasoning
2958. NeurIPS 2024Interpretable Generalized Additive Models for Datasets with Missing Values
2959. NeurIPS 2024Interpretable Image Classification with Adaptive Prototype-based Vision Transformers
2960. NeurIPS 2024Interpretable Mesomorphic Networks for Tabular Data
2961. NeurIPS 2024Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledge
2962. NeurIPS 2024Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
2963. NeurIPS 2024Interpreting Learned Feedback Patterns in Large Language Models
2964. NeurIPS 2024Intervention and Conditioning in Causal Bayesian Networks
2965. NeurIPS 2024InversionView: A General-Purpose Method for Reading Information from Neural Activations
2966. NeurIPS 2024Is the MMI Criterion Necessary for Interpretability? Degenerating Non-causal Features to Plain Noise for Self-Rationalization
2967. NeurIPS 2024Iteration Head: A Mechanistic Study of Chain-of-Thought
2968. NeurIPS 2024Language Model as Visual Explainer
2969. NeurIPS 2024Learnability of high-dimensional targets by two-parameter models and gradient flow
2970. NeurIPS 2024Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios
2971. NeurIPS 2024Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
2972. NeurIPS 2024Learning Place Cell Representations and Context-Dependent Remapping
2973. NeurIPS 2024Learning Social Welfare Functions
2974. NeurIPS 2024Learning the Latent Causal Structure for Modeling Label Noise
2975. NeurIPS 2024Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
2976. NeurIPS 2024Learning to Understand: Identifying Interactions via the Möbius Transform
2977. NeurIPS 2024Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems
2978. NeurIPS 2024LG-CAV: Train Any Concept Activation Vector with Language Guidance
2979. NeurIPS 2024Linear Transformers are Versatile In-Context Learners
2980. NeurIPS 2024Linking In-context Learning in Transformers to Human Episodic Memory
2981. NeurIPS 2024Listenable Maps for Zero-Shot Audio Classifiers
2982. NeurIPS 2024LLM Circuit Analyses Are Consistent Across Training and Scale
2983. NeurIPS 2024Local to Global: Learning Dynamics and Effect of Initialization for Transformers
2984. NeurIPS 2024Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
2985. NeurIPS 2024MambaLRP: Explaining Selective State Space Sequence Models
2986. NeurIPS 2024Measuring Per-Unit Interpretability at Scale Without Humans
2987. NeurIPS 2024Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
2988. NeurIPS 2024MeLLoC: Lossless Compression with High-order Mechanism Learning
2989. NeurIPS 2024Microstructures and Accuracy of Graph Recall by Large Language Models
2990. NeurIPS 2024Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
2991. NeurIPS 2024Model Based Inference of Synaptic Plasticity Rules
2992. NeurIPS 2024Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks
2993. NeurIPS 2024Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory
2994. NeurIPS 2024Most Influential Subset Selection: Challenges, Promises, and Beyond
2995. NeurIPS 2024Motif-oriented influence maximization for viral marketing in large-scale social networks
2996. NeurIPS 2024MTGS: A Novel Framework for Multi-Person Temporal Gaze Following and Social Gaze Prediction
2997. NeurIPS 2024Multi-Winner Reconfiguration
2998. NeurIPS 2024Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
2999. NeurIPS 2024Navigating the Effect of Parametrization for Dimensionality Reduction
3000. NeurIPS 2024Neural Concept Binder

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。