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 4 / 11 页

151. NeurIPS 2025Emergent Risk Awareness in Rational Agents under Resource Constraints
152. NeurIPS 2025Empowering Decision Trees via Shape Function Branching
153. NeurIPS 2025Enhancing Interpretability in Deep Reinforcement Learning through Semantic Clustering
154. NeurIPS 2025Epistemic Uncertainty for Generated Image Detection
155. NeurIPS 2025Erasing Conceptual Knowledge from Language Models
156. NeurIPS 2025ErrorTrace: A Black-Box Traceability Mechanism Based on Model Family Error Space
157. NeurIPS 2025Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
158. NeurIPS 2025Estimation of Treatment Effects in Extreme and Unobserved Data
159. NeurIPS 2025Evaluating LLMs in Open-Source Games
160. NeurIPS 2025EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions
161. NeurIPS 2025Explaining and Mitigating Crosslingual Tokenizer Inequities
162. NeurIPS 2025Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions
163. NeurIPS 2025Exploring Semantic-constrained Adversarial Example with Instruction Uncertainty Reduction
164. NeurIPS 2025Exploring the limits of strong membership inference attacks on large language models
165. NeurIPS 2025Exploring the Translation Mechanism of Large Language Models
166. NeurIPS 2025FACE: Faithful Automatic Concept Extraction
167. NeurIPS 2025FaCT: Faithful Concept Traces for Explaining Neural Network Decisions
168. NeurIPS 2025Fair Continuous Resource Allocation with Equality of Impact
169. NeurIPS 2025Fair Deepfake Detectors Can Generalize
170. NeurIPS 2025Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
171. NeurIPS 2025Fairness under Competition
172. NeurIPS 2025Fairness-aware Bayes Optimal Functional Classification
173. NeurIPS 2025FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
174. NeurIPS 2025Fairshare Data Pricing via Data Valuation for Large Language Models
175. NeurIPS 2025Faithful Group Shapley Value
176. NeurIPS 2025FALCON: Fine-grained Activation Manipulation by Contrastive Orthogonal Unalignment for Large Language Model
177. NeurIPS 2025Fast Computation and Optimization for Opinion-Based Quantities of Friedkin-Johnsen Model
178. NeurIPS 2025FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
179. NeurIPS 2025FedRACE: A Hierarchical and Statistical Framework for Robust Federated Learning
180. NeurIPS 2025FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
181. NeurIPS 2025Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods
182. NeurIPS 2025Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
183. NeurIPS 2025Fix False Transparency by Noise Guided Splatting
184. NeurIPS 2025Fixing It in Post: A Comparative Study of LLM Post-Training Data Quality and Model Performance
185. NeurIPS 2025FlexAC: Towards Flexible Control of Associative Reasoning in Multimodal Large Language Models
186. NeurIPS 2025FlowMixer: A Depth-Agnostic Neural Architecture for Interpretable Spatiotemporal Forecasting
187. NeurIPS 2025FlowPrune: Accelerating Attention Flow Calculation by Pruning Flow Network
188. NeurIPS 2025FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
189. NeurIPS 2025For Better or for Worse, Transformers Seek Patterns for Memorization
190. NeurIPS 2025Fostering the Ecosystem of AI for Social Impact Requires Expanding and Strengthening Evaluation Standards
191. NeurIPS 2025From Black-box to Causal-box: Towards Building More Interpretable Models
192. NeurIPS 2025From Counterfactuals to Trees: Competitive Analysis of Model Extraction Attacks
193. NeurIPS 2025From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit
194. NeurIPS 2025From Judgment to Interference: Early Stopping LLM Harmful Outputs via Streaming Content Monitoring
195. NeurIPS 2025From Noise to Narrative: Tracing the Origins of Hallucinations in Transformers
196. NeurIPS 2025From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes
197. NeurIPS 2025Fundamental Limitations in Pointwise Defences of LLM Finetuning APIs
198. NeurIPS 2025Generative Model Inversion Through the Lens of the Manifold Hypothesis
199. NeurIPS 2025Generative RLHF-V: Learning Principles from Multi-modal Human Preference
200. NeurIPS 2025GeoClip: Geometry-Aware Clipping for Differentially Private SGD

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。