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 43 / 69 页

2101. NeurIPS 2025CVGL: Causal Learning and Geometric Topology
2102. NeurIPS 2025Data-Free Model Extraction for Black-box Recommender Systems via Graph Convolutions
2103. NeurIPS 2025Deep Learning with Plausible Deniability
2104. NeurIPS 2025Deep Value Benchmark: Measuring Whether Models Generalize Deep values or Shallow Preferences
2105. NeurIPS 2025Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
2106. NeurIPS 2025Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
2107. NeurIPS 2025DEGauss: Defending Against Malicious 3D Editing for Gaussian Splatting
2108. NeurIPS 2025Dense SAE Latents Are Features, Not Bugs
2109. NeurIPS 2025DePass: Unified Feature Attributing by Simple Decomposed Forward Pass
2110. NeurIPS 2025DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
2111. NeurIPS 2025Detecting Generated Images by Fitting Natural Image Distributions
2112. NeurIPS 2025Detecting High-Stakes Interactions with Activation Probes
2113. NeurIPS 2025Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing
2114. NeurIPS 2025DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control
2115. NeurIPS 2025DictPFL: Efficient and Private Federated Learning on Encrypted Gradients
2116. NeurIPS 2025DiffBreak: Is Diffusion-Based Purification Robust?
2117. NeurIPS 2025Differentiable Sparsity via $D$-Gating: Simple and Versatile Structured Penalization
2118. NeurIPS 2025Differential Privacy on Fully Dynamic Streams
2119. NeurIPS 2025Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
2120. NeurIPS 2025Differentially Private Gomory-Hu Trees
2121. NeurIPS 2025Differentially Private High-dimensional Variable Selection via Integer Programming
2122. NeurIPS 2025Differentially Private Quantiles with Smaller Error
2123. NeurIPS 2025Differentially Private Relational Learning with Entity-level Privacy Guarantees
2124. NeurIPS 2025Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive
2125. NeurIPS 2025Dimensionality Mismatch Between Brains and Artificial Neural Networks
2126. NeurIPS 2025Direct Alignment with Heterogeneous Preferences
2127. NeurIPS 2025Discovering Opinion Intervals from Conflicts in Signed Graphs
2128. NeurIPS 2025Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
2129. NeurIPS 2025Disentangling Superpositions: Interpretable Brain Encoding Model with Sparse Concept Atoms
2130. NeurIPS 2025Distillation Robustifies Unlearning
2131. NeurIPS 2025DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
2132. NeurIPS 2025Do different prompting methods yield a common task representation in language models?
2133. NeurIPS 2025Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
2134. NeurIPS 2025Does Object Binding Naturally Emerge in Large Pretrained Vision Transformers?
2135. NeurIPS 2025Does Representation Guarantee Welfare?
2136. NeurIPS 2025Don’t Give Up on Democratizing AI for the Wrong Reasons
2137. NeurIPS 2025Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the Role of Model Complexity
2138. NeurIPS 2025DPA: A one-stop metric to measure bias amplification in classification datasets
2139. NeurIPS 2025DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents
2140. NeurIPS 2025DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testing
2141. NeurIPS 2025DualOptim: Enhancing Efficacy and Stability in Machine Unlearning with Dual Optimizers
2142. NeurIPS 2025E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
2143. NeurIPS 2025EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification
2144. NeurIPS 2025EAReranker: Efficient Embedding Adequacy Assessment for Retrieval Augmented Generation
2145. NeurIPS 2025Efficient Algorithms for Robust and Partial Semi-Discrete Optimal Transport
2146. NeurIPS 2025Efficient Fairness-Performance Pareto Front Computation
2147. NeurIPS 2025Efficient Utility-Preserving Machine Unlearning with Implicit Gradient Surgery
2148. NeurIPS 2025ElliCE: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets
2149. NeurIPS 2025Emergence and Evolution of Interpretable Concepts in Diffusion Models
2150. NeurIPS 2025Emergent Risk Awareness in Rational Agents under Resource Constraints

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。