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 38 / 69 页

1851. ICML 2025MixBridge: Heterogeneous Image-to-Image Backdoor Attack through Mixture of Schrödinger Bridges
1852. ICML 2025Mixture of Experts Made Intrinsically Interpretable
1853. ICML 2025MP-Nav: Enhancing Data Poisoning Attacks against Multimodal Learning
1854. ICML 2025Multiaccuracy and Multicalibration via Proxy Groups
1855. ICML 2025Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning
1856. ICML 2025Near-Optimal Decision Trees in a SPLIT Second
1857. ICML 2025Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
1858. ICML 2025Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
1859. ICML 2025Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails
1860. ICML 2025Not All Wrong is Bad: Using Adversarial Examples for Unlearning
1861. ICML 2025Omni-Angle Assault: An Invisible and Powerful Physical Adversarial Attack on Face Recognition
1862. ICML 2025On Explaining Equivariant Graph Networks via Improved Relevance Propagation
1863. ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
1864. ICML 2025On the Benefits of Active Data Collection in Operator Learning
1865. ICML 2025On the Impact of Performative Risk Minimization for Binary Random Variables
1866. ICML 2025On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
1867. ICML 2025On the Private Estimation of Smooth Transport Maps
1868. ICML 2025On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
1869. ICML 2025One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
1870. ICML 2025Optimal and Practical Batched Linear Bandit Algorithm
1871. ICML 2025Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
1872. ICML 2025Optimal Fair Learning Robust to Adversarial Distribution Shift
1873. ICML 2025Optimizing Adaptive Attacks against Watermarks for Language Models
1874. ICML 2025Optimizing Noise Distributions for Differential Privacy
1875. ICML 2025Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
1876. ICML 2025OR-Bench: An Over-Refusal Benchmark for Large Language Models
1877. ICML 2025Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
1878. ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
1879. ICML 2025Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
1880. ICML 2025Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
1881. ICML 2025Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
1882. ICML 2025Policy Design for Two-sided Platforms with Participation Dynamics
1883. ICML 2025POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimization
1884. ICML 2025Position: AI Agents Need Authenticated Delegation
1885. ICML 2025Position: AI Safety should prioritize the Future of Work
1886. ICML 2025Position: AI's growing due process problem
1887. ICML 2025Position: Build Agent Advocates, Not Platform Agents
1888. ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
1889. ICML 2025Position: Contextual Integrity is Inadequately Applied to Language Models
1890. ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
1891. ICML 2025Position: Explainable AI Cannot Advance Without Better User Studies
1892. ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
1893. ICML 2025Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
1894. ICML 2025Position: Language model developers should report train-test overlap
1895. ICML 2025Position: Machine Learning Models Have a Supply Chain Problem
1896. ICML 2025Position: Rethinking Explainable Machine Learning as Applied Statistics
1897. ICML 2025Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
1898. ICML 2025Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
1899. ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
1900. ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process

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。