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 1,275 篇，第 16 / 26 页

751. NeurIPS 2025Performative Validity of Recourse Explanations
752. NeurIPS 2025Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
753. NeurIPS 2025Pinpointing Attention-Causal Communication in Language Models
754. NeurIPS 2025Position: If Innovation in AI systematically Violates Fundamental Rights, Is It Innovation at All?
755. NeurIPS 2025Position: Require Frontier AI Labs To Release Small "Analog" Models
756. NeurIPS 2025Practical Bayes-Optimal Membership Inference Attacks
757. NeurIPS 2025Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
758. NeurIPS 2025Predicting the Performance of Black-box Language Models with Follow-up Queries
759. NeurIPS 2025Prior Forgetting and In-Context Overfitting
760. NeurIPS 2025Privacy amplification by random allocation
761. NeurIPS 2025Private Continual Counting of Unbounded Streams
762. NeurIPS 2025Private Geometric Median in Nearly-Linear Time
763. NeurIPS 2025Private Hyperparameter Tuning with Ex-Post Guarantee
764. NeurIPS 2025Private Set Union with Multiple Contributions
765. NeurIPS 2025Private Zeroth-Order Optimization with Public Data
766. NeurIPS 2025Probabilistic Stability Guarantees for Feature Attributions
767. NeurIPS 2025Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry
768. NeurIPS 2025ProtoPairNet: Interpretable Regression through Prototypical Pair Reasoning
769. NeurIPS 2025Provable Gradient Editing of Deep Neural Networks
770. NeurIPS 2025Proxy-SPEX: Sample-Efficient Interpretability via Sparse Feature Interactions in LLMs
771. NeurIPS 2025Purifying Approximate Differential Privacy with Randomized Post-processing
772. NeurIPS 2025Quantifying Cross-Modality Memorization in Vision-Language Models
773. NeurIPS 2025Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
774. NeurIPS 2025Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2
775. NeurIPS 2025Reasoning Models Sometimes Output Illegible Chains of Thought
776. NeurIPS 2025Rectifying Shortcut Behaviors in Preference-based Reward Learning
777. NeurIPS 2025Redefining Experts: Interpretable Decomposition of Language Models for Toxicity Mitigation
778. NeurIPS 2025Regional Explanations: Bridging Local and Global Variable Importance
779. NeurIPS 2025Regression Trees Know Calculus
780. NeurIPS 2025Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
781. NeurIPS 2025Removing Concepts from Text-to-Image Models with Only Negative Samples
782. NeurIPS 2025Replicable Online pricing
783. NeurIPS 2025Representational Difference Explanations
784. NeurIPS 2025Rescaled Influence Functions: Accurate Data Attribution in High Dimension
785. NeurIPS 2025Residual Stream Analysis of Overfitting And Structural Disruptions
786. NeurIPS 2025Rethinking Circuit Completeness in Language Models: AND, OR, and ADDER Gates
787. NeurIPS 2025Rethinking Fair Federated Learning from Parameter and Client View
788. NeurIPS 2025Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
789. NeurIPS 2025Rethinking the Role of Verbatim Memorization in LLM Privacy
790. NeurIPS 2025Revising and Falsifying Sparse Autoencoder Feature Explanations
791. NeurIPS 2025Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability
792. NeurIPS 2025Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
793. NeurIPS 2025Ridge Boosting is Both Robust and Efficient
794. NeurIPS 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
795. NeurIPS 2025Robust and Scalable Autonomous Reinforcement Learning in Irreversible Environments
796. NeurIPS 2025Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
797. NeurIPS 2025Robust Explanations of Graph Neural Networks via Graph Curvatures
798. NeurIPS 2025Robust Integrated Learning and Pauli Noise Mitigation for Parametrized Quantum Circuits
799. NeurIPS 2025Robust SuperAlignment: Weak-to-Strong Robustness Generalization for Vision-Language Models
800. NeurIPS 2025RUAGO: Effective and Practical Retain-Free Unlearning via Adversarial Attack and OOD Generator

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。