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 522 篇，第 7 / 11 页

301. NeurIPS 2025MOTION: Multi-Sculpt Evolutionary Coarsening for Federated Continual Graph Learning
302. NeurIPS 2025MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
303. NeurIPS 2025Multi-Class Support Vector Machine with Differential Privacy
304. NeurIPS 2025Multi-order Orchestrated Curriculum Distillation for Model-Heterogeneous Federated Graph Learning
305. NeurIPS 2025Multidimensional Bayesian Utility Maximization: Tight Approximations to Welfare
306. NeurIPS 2025Neural Collapse is Globally Optimal in Deep Regularized ResNets and Transformers
307. NeurIPS 2025Neural Correlates of Serial Dependence: Synaptic Short-term Plasticity Orchestrates Repulsion and Attraction
308. NeurIPS 2025Neural Rule Lists: Learning Discretizations, Rules, and Order in One Go
309. NeurIPS 2025Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models
310. NeurIPS 2025Nonlinearly Preconditioned Gradient Methods: Momentum and Stochastic Analysis
311. NeurIPS 2025OASIS: One-Shot Federated Graph Learning via Wasserstein Assisted Knowledge Integration
312. NeurIPS 2025Object-Centric Concept-Bottlenecks
313. NeurIPS 2025Obliviator Reveals the Cost of Nonlinear Guardedness in Concept Erasure
314. NeurIPS 2025On Group Sufficiency Under Label Bias
315. NeurIPS 2025On Learning Verifiers and Implications to Chain-of-Thought Reasoning
316. NeurIPS 2025On Logic-based Self-Explainable Graph Neural Networks
317. NeurIPS 2025On Optimal Steering to Achieve Exact Fairness
318. NeurIPS 2025On the Coexistence and Ensembling of Watermarks
319. NeurIPS 2025On the creation of narrow AI: hierarchy and nonlocality of neural network skills
320. NeurIPS 2025On the Existence and Complexity of Core-Stable Data Exchanges
321. NeurIPS 2025On the Sample Complexity of Differentially Private Policy Optimization
322. NeurIPS 2025On the Stability and Generalization of Meta-Learning: the Impact of Inner-Levels
323. NeurIPS 2025One Head to Rule Them All: Amplifying LVLM Safety through a Single Critical Attention Head
324. NeurIPS 2025One Token Embedding Is Enough to Deadlock Your Large Reasoning Model
325. NeurIPS 2025One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models
326. NeurIPS 2025Online Strategic Classification With Noise and Partial Feedback
327. NeurIPS 2025OOD Detection with Relative Angles
328. NeurIPS 2025OpenGU: A Comprehensive Benchmark for Graph Unlearning
329. NeurIPS 2025OrdShap: Feature Position Importance for Sequential Black-Box Models
330. NeurIPS 2025Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning
331. NeurIPS 2025Pairwise Calibrated Rewards for Pluralistic Alignment
332. NeurIPS 2025Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation
333. NeurIPS 2025Part-Aware Bottom-Up Group Reasoning for Fine-Grained Social Interaction Detection
334. NeurIPS 2025Path-specific effects for pulse-oximetry guided decisions in critical care
335. NeurIPS 2025Performative Validity of Recourse Explanations
336. NeurIPS 2025Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
337. NeurIPS 2025Pinpointing Attention-Causal Communication in Language Models
338. NeurIPS 2025Position: If Innovation in AI systematically Violates Fundamental Rights, Is It Innovation at All?
339. NeurIPS 2025Position: Require Frontier AI Labs To Release Small "Analog" Models
340. NeurIPS 2025Practical Bayes-Optimal Membership Inference Attacks
341. NeurIPS 2025Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
342. NeurIPS 2025Predicting the Performance of Black-box Language Models with Follow-up Queries
343. NeurIPS 2025Prior Forgetting and In-Context Overfitting
344. NeurIPS 2025Privacy amplification by random allocation
345. NeurIPS 2025Private Continual Counting of Unbounded Streams
346. NeurIPS 2025Private Geometric Median in Nearly-Linear Time
347. NeurIPS 2025Private Hyperparameter Tuning with Ex-Post Guarantee
348. NeurIPS 2025Private Set Union with Multiple Contributions
349. NeurIPS 2025Private Zeroth-Order Optimization with Public Data
350. NeurIPS 2025Probabilistic Stability Guarantees for Feature Attributions

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。