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 65 / 69 页

3201. ICLR 2023HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings
3202. ICLR 2023Holistic Adversarially Robust Pruning
3203. ICLR 2023How I Learned to Stop Worrying and Love Retraining
3204. ICLR 2023How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
3205. ICLR 2023How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections
3206. ICLR 2023Inequality phenomenon in $l_{\infty}$-adversarial training, and its unrealized threats
3207. ICLR 2023Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small
3208. ICLR 2023Interpretability with full complexity by constraining feature information
3209. ICLR 2023Label-free Concept Bottleneck Models
3210. ICLR 2023Learning Vortex Dynamics for Fluid Inference and Prediction
3211. ICLR 2023Learning without Prejudices: Continual Unbiased Learning via Benign and Malignant Forgetting
3212. ICLR 2023LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification
3213. ICLR 2023Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes
3214. ICLR 2023Martingale Posterior Neural Processes
3215. ICLR 2023Mind the Pool: Convolutional Neural Networks Can Overfit Input Size
3216. ICLR 2023MultiViz: Towards Visualizing and Understanding Multimodal Models
3217. ICLR 2023On Accelerated Perceptrons and Beyond
3218. ICLR 2023On Explaining Neural Network Robustness with Activation Path
3219. ICLR 2023On The Inadequacy of Optimizing Alignment and Uniformity in Contrastive Learning of Sentence Representations
3220. ICLR 2023On The Specialization of Neural Modules
3221. ICLR 2023On the Trade-Off between Actionable Explanations and the Right to be Forgotten
3222. ICLR 2023PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs
3223. ICLR 2023Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
3224. ICLR 2023Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
3225. ICLR 2023Post-hoc Concept Bottleneck Models
3226. ICLR 2023Progress measures for grokking via mechanistic interpretability
3227. ICLR 2023Riemannian Metric Learning via Optimal Transport
3228. ICLR 2023Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation
3229. ICLR 2023Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions
3230. ICLR 2023Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning
3231. ICLR 2023Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
3232. ICLR 2023Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees
3233. ICLR 2023TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization
3234. ICLR 2023Training language models to summarize narratives improves brain alignment
3235. ICLR 2023Understanding and Adopting Rational Behavior by Bellman Score Estimation
3236. ICML 2023A Closer Look at the Intervention Procedure of Concept Bottleneck Models
3237. ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
3238. ICML 2023A Law of Robustness beyond Isoperimetry
3239. ICML 2023A Modern Look at the Relationship between Sharpness and Generalization
3240. ICML 2023A Study on Transformer Configuration and Training Objective
3241. ICML 2023A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations
3242. ICML 2023abess: A Fast Best-Subset Selection Library in Python and R
3243. ICML 2023AdaBoost is not an Optimal Weak to Strong Learner
3244. ICML 2023Adaptive Coordination in Social Embodied Rearrangement
3245. ICML 2023Adversarial Classification: Necessary Conditions and Geometric Flows
3246. ICML 2023Are Equivariant Equilibrium Approximators Beneficial?
3247. ICML 2023Bandit Online Linear Optimization with Hints and Queries
3248. ICML 2023Bandits with Knapsacks: Advice on Time-Varying Demands
3249. ICML 2023Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts
3250. ICML 2023Better Training of GFlowNets with Local Credit and Incomplete Trajectories

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。