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 12 / 69 页

551. ICML 2026Domain Restriction via SAE Multi-Layer Transitions
552. ICML 2026DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning
553. ICML 2026DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole Slide Image Survival Prediction
554. ICML 2026Drop-in Circulant Structural Priors for Transformer Decoding of Cyclic Codes
555. ICML 2026Dual Mechanisms of Value Expression: Intrinsic vs. Prompted Values in Large Language Models
556. ICML 2026Dual-branch Robust Unlearnable Examples
557. ICML 2026DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models
558. ICML 2026Dynamic Linear Attention
559. ICML 2026Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure
560. ICML 2026ECCO: Evidence-Driven Causal Reasoning for Compiler Optimization
561. ICML 2026Echoes within the Reasoning: Stealthy and Effective Watermarking via Chain of Thought
562. ICML 2026Efficient Bayesian Inference from Noisy Pairwise Comparisons
563. ICML 2026Efficient LLM Moderation with Multi-Layer Latent Prototypes
564. ICML 2026Efficient privacy loss accounting for subsampling and random allocation
565. ICML 2026Efficient Public Verification of Private ML via Regularization
566. ICML 2026Eliminating Solution Bias in Differentially Private Optimization
567. ICML 2026Emergence of Hierarchical Emotion Organization in Large Language Models
568. ICML 2026Emergent Analogical Reasoning in Transformers
569. ICML 2026Emergent Communication Under Misinformation
570. ICML 2026Endogenous Resistance to Activation Steering in Language Models
571. ICML 2026Enhancing Conformal Prediction via Class Similarity
572. ICML 2026Ensembling Sparse Autoencoders
573. ICML 2026EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors
574. ICML 2026Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
575. ICML 2026Evaluating and Steering Modality Preferences in Multi-modal LLMs
576. ICML 2026Every Step Counts: Decoding Trajectories as Authorship Fingerprints of dLLMs
577. ICML 2026Evidential Copula Concept Embedding Models
578. ICML 2026Exact and Approximate Algorithms for Polytree Learning
579. ICML 2026Exact Functional ANOVA Decomposition for Categorical Inputs Models
580. ICML 2026Exactly Computing do-Shapley Values
581. ICML 2026Expand Neurons, Not Parameters
582. ICML 2026Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
583. ICML 2026ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior
584. ICML 2026Explanations are a Means to an End: Decision Theoretic Explanation Evaluation
585. ICML 2026Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
586. ICML 2026Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search
587. ICML 2026Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
588. ICML 2026Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
589. ICML 2026Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
590. ICML 2026Fair Dataset Distillation via Cross-Group Barycenter Alignment
591. ICML 2026Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
592. ICML 2026Fair Transit Stop Placement: A Clustering Perspective and Beyond
593. ICML 2026FairGB: A Fair Granular-Ball Generation Method for Data Classification
594. ICML 2026Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
595. ICML 2026FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
596. ICML 2026FakeWorld 1.0: An Omni-modal Benchmark for Fake Media and Content
597. ICML 2026Falling Trees: A Model Class for Interpretable Risk Prioritization
598. ICML 2026Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process
599. ICML 2026Fast and Near-Optimal Algorithms for Private Hypothesis Selection
600. ICML 2026Fast and Scalable Analytical Diffusion

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。