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 4 / 13 页

151. ICLR 2026Learning to Interpret Weight Differences in Language Models
152. ICLR 2026Learning to Lie: Adversarial Attacks on Human-AI Teams and LLMs
153. ICLR 2026Learning to Weight Parameters for Training Data Attribution
154. ICLR 2026LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?
155. ICLR 2026LLMs Process Lists With General Filter Heads
156. ICLR 2026Localizing Task Recognition and Task Learning in In-Context Learning via Attention Head Analysis
157. ICLR 2026LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks
158. ICLR 2026Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry
159. ICLR 2026Matched Data, Better Models: Target Aligned Data Filtering with Sparse Features
160. ICLR 2026MCbiF: Measuring Topological Autocorrelation in Multiscale Clusterings via 2-Parameter Persistent Homology
161. ICLR 2026Mechanism of Task-oriented Information Removal in In-context Learning
162. ICLR 2026Mechanistic Detection and Mitigation of Hallucination in Large Reasoning Models
163. ICLR 2026Medical Interpretability and Knowledge Maps of Large Language Models
164. ICLR 2026Misaligned Roles, Misplaced Images: Structural Input Perturbations Expose Multimodal Alignment Blind Spots
165. ICLR 2026Missingness Bias Calibration in Feature Attribution Explanations
166. ICLR 2026Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context
167. ICLR 2026Multi-Feature Quantized Self-Attention for Fair Large Language Models
168. ICLR 2026Multilingual Routing in Mixture-of-Experts
169. ICLR 2026Multiple Streams of Knowledge Retrieval: Enriching and Recalling in Transformers
170. ICLR 2026Multiple Token Divergence: Measuring and Steering In-Context Computation Density
171. ICLR 2026Narrow Finetuning Leaves Clearly Readable Traces in the Activation Differences
172. ICLR 2026NatADiff: Adversarial Boundary Guidance for Natural Adversarial Diffusion
173. ICLR 2026Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams
174. ICLR 2026Negative Pre-activations Differentiate Syntax
175. ICLR 2026Neologism Learning for Controllability and Self-Verbalization
176. ICLR 2026Neural Synchrony Between Socially Interacting Language Models
177. ICLR 2026Neural+Symbolic Approaches for Interpretable Actor-Critic Reinforcement Learning
178. ICLR 2026Neuron-Aware Data Selection in Instruction Tuning for Large Language Models
179. ICLR 2026Neuron-Level Analysis of Cultural Understanding in Large Language Models
180. ICLR 2026Newton Method Revisited: Global Convergence Rates up to $O(1/k^3)$ for Stepsize Schedules and Linesearch Procedures
181. ICLR 2026Neyman-Pearson Classification under Both Null and Alternative Distributions Shift
182. ICLR 2026NIMO: a Nonlinear Interpretable MOdel
183. ICLR 2026Null-Space Filtering for Data-free Continual Model Merging: Preserving Transparency, Promoting Fidelity
184. ICLR 2026Obfuscated Activations Bypass LLM Latent-Space Defenses
185. ICLR 2026Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research
186. ICLR 2026On Predictability of Reinforcement Learning Dynamics for Large Language Models
187. ICLR 2026On the Expressiveness of State Space Models via Temporal Logics
188. ICLR 2026On the Impact of the Utility in Semivalue-based Data Valuation
189. ICLR 2026On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy
190. ICLR 2026On the Predictive Power of Representation Dispersion in Language Models
191. ICLR 2026On the Spectral Differences Between NTK and CNTK and Their Implications for Point Cloud Recognition
192. ICLR 2026Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits
193. ICLR 2026Oversmoothing, "Oversquashing'', Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
194. ICLR 2026Paradigm Shift of GNN Explainer from Label Space to Prototypical Representation Space
195. ICLR 2026Path Channels and Plan Extension Kernels: a Mechanistic Description of Planning in a Sokoban RNN
196. ICLR 2026Patronus: Interpretable Diffusion Models with Prototypes
197. ICLR 2026PerFit: Exploring Personalization Shifts in Representation Space of LLMs
198. ICLR 2026PlantRSR: A New Plant Dataset and Method for Reference-based Super-Resolution
199. ICLR 2026Polynomial, trigonometric, and tropical activations
200. ICLR 2026PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression

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。