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 541 篇，第 2 / 11 页

51. ICML 2026AutoBaxBuilder: Bootstrapping Code Security Benchmarking
52. ICML 2026Automatically Finding Reward Model Biases
53. ICML 2026Balancing Plasticity and Stability with Fast and Slow Successor Features
54. ICML 2026Bandit Social Leaning Dynamics with Exploration Episodes
55. ICML 2026Base Models Know How to Reason, Thinking Models Learn When
56. ICML 2026Bayesian Gated Non-Negative Contrastive Learning
57. ICML 2026Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
58. ICML 2026Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting
59. ICML 2026Beyond Additive Decompositions: Interpretability Through Separability
60. ICML 2026Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring
61. ICML 2026Beyond Literal Translation: Evaluating Cultural Effectiveness in Social Media UGC
62. ICML 2026Beyond Pixels: Mining Compressed Domain Artifacts for Efficient AI-Generated Video Detection
63. ICML 2026Beyond Procedure: Substantive Fairness in Conformal Prediction
64. ICML 2026Beyond Sample-Level Forgetting: Improving Reliability in Multimodal Unlearning
65. ICML 2026Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability
66. ICML 2026Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability
67. ICML 2026Biases in the Blind Spot: Detecting What LLMs Fail to Mention
68. ICML 2026Black-Box Assisted Regression: Phase Transitions and Minimax Optimality
69. ICML 2026Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking
70. ICML 2026Brain Networks Should Be Learned, Not Constructed
71. ICML 2026Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
72. ICML 2026Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL
73. ICML 2026Broadening the Backdoor Basin: Understanding LLM Backdoors Collapse and Making Backdoors Persistent
74. ICML 2026Building Reliable Long-Form Generation via Hallucination Rejection Sampling
75. ICML 2026Building Social World Model with Large Language Models
76. ICML 2026C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
77. ICML 2026CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
78. ICML 2026CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting
79. ICML 2026Catch-22: On the Fundamental Tradeoff Between Detectability and Robustness in LLM Watermarking
80. ICML 2026Categorical Reparameterization with Denoising Diffusion Models
81. ICML 2026Causal Detection of Multi-Step LLM Agent Attacks
82. ICML 2026CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution
83. ICML 2026CausalX: A Unified and Causally-Interpretable Plug-and-Play Model for Multi-modal Spatio-Temporal Forecasting
84. ICML 2026CausalXRL: Explainable Reinforcement Learning through Causal Graph Reasoning
85. ICML 2026Causes and Consequences of Representational Similarity in Machine Learning Models
86. ICML 2026CB-SLICE: Concept-Based Interpretable Error Slice Discovery
87. ICML 2026Censoring with Plausible Deniability: Asymmetric Local Privacy for Multi-Category CDF Estimation
88. ICML 2026Cert-LAS: Toward Certified Model Ownership Verification for Text-to-Image Diffusion Models via Layer-Adaptive Smoothing
89. ICML 2026Certified Circuits: Stability Guarantees for Mechanistic Circuits
90. ICML 2026Chain-of-Thought Reasoning In The Wild Is Not Always Faithful
91. ICML 2026CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
92. ICML 2026Cold-Start Personalization via Bayesian Adaptive Questioning
93. ICML 2026Collaborative Threshold Watermarking
94. ICML 2026ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution
95. ICML 2026Conflict-Aware Adaptive Alignment for LLM Hallucination Mitigation
96. ICML 2026Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
97. ICML 2026Consistency Training Can Entrench Misalignment
98. ICML 2026Contextual Slate GLM Bandits with Limited Adaptivity
99. ICML 2026Continual Learning With Participation Privacy: An Auditable Buffering-Aggregation Recipe
100. ICML 2026Contribution Weights: A Geometrical Analysis of Self-Attention Transformers

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。