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 416 篇，第 1 / 9 页

1. NeurIPS 2026$\mathcal{P}$Torch: Narrowing the Gap Between Projection and Gradient-Based Learning
2. NeurIPS 2026A Critical $\beta$-Scale for Posterior Collapse in Dirichlet $\beta$-VAEs
3. NeurIPS 2026A Mechanistic Interpretability Study of an Astronomical Foundation Model
4. NeurIPS 2026A simple model of co-emergence of grid and place fields
5. NeurIPS 2026A Unifying Perspective on Language Model Interpretability
6. NeurIPS 2026Achieving Optimal Static and Dynamic Regret Simultaneously in Bandits with Deterministic Losses
7. NeurIPS 2026Adapting to Conflict: Equilibrium Structure and Adaptive Learning in Harmonic Games
8. NeurIPS 2026AdKnob: Ad Intensity Control and Labeling for LLM-Native Advertising
9. NeurIPS 2026Agentic AI Design Should be Mediated to Promote Social Welfare
10. NeurIPS 2026Agentic-imodels: Evolving agentic interpretability tools via autoresearch
11. NeurIPS 2026AI-Assisted Classification under Correlation Neglect and Trust
12. NeurIPS 2026AI-Mediated Communication Can Steer Collective Opinion
13. NeurIPS 2026Algorithms for Linear Equations with Min and Max Operators Under (Absolutely) Halting Condition
14. NeurIPS 2026Amortized Linear-time Exact Shapley Value for Product-Kernel Methods
15. NeurIPS 2026An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration
16. NeurIPS 2026An Axiomatic Analysis of DPO and NLHF as Reference-Dependent Probabilistic Voting Rules
17. NeurIPS 2026Are Well-Trained Surrogates Optimal? Rethinking the Surrogate Role with Instability for Unlearnable Examples
18. NeurIPS 2026Assessing Per-Sample Membership Inference Vulnerability without Retraining
19. NeurIPS 2026Assign and Add: A Mechanistic Study of Compositional Arithmetic
20. NeurIPS 2026Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
21. NeurIPS 2026Auditor-Assisted Summary-Channel Verification for Hosted LLM Identity Substitution
22. NeurIPS 2026AutoHoney: Automating, Deploying, and Evaluating Scheming Honeypots Across Production Codebases
23. NeurIPS 2026Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds
24. NeurIPS 2026BarrierSteer: LLM Safety via Learning Barrier Steering
25. NeurIPS 2026BEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation
26. NeurIPS 2026Before Words, Beyond Speech: Evaluating Nonverbal Social Reasoning in Early Childhood
27. NeurIPS 2026Bentkus-type asymptotic e-values
28. NeurIPS 2026Beyond Confidence: Rethinking Self-Assessments for Performance Prediction in LLMs
29. NeurIPS 2026Beyond Feature Disruption: Boundary-Diverting Unlearnable Examples against Linear Probing
30. NeurIPS 2026Beyond Interpretability: When, Why, and How Sparse Autoencoders Enable Label-Free Visual Steering
31. NeurIPS 2026Beyond Isotropy in JEPAs: Hamiltonian Geometry and Symplectic Prediction
32. NeurIPS 2026Beyond Success Rates: Trainability and Extractability in Offline GCRL
33. NeurIPS 2026Beyond the Half Approximation: Fair and Efficient Online Class Matching
34. NeurIPS 2026Beyond the Prompt: Leveraging Pre-Decoding States for Jailbreak Detection in dLLMs
35. NeurIPS 2026BIAS-ID: A Framework for Analyzing Transformation Biases in AI-Generated Image Detectors
36. NeurIPS 2026Bias, Measurement Error, and Double-Dipping: When Can GNN Convolutions Help Brain Connectome Prediction?
37. NeurIPS 2026BiasTrojan: LLM Judgers Are Easily Distorted by Few Hundreds of Contrastive Biased Training Data
38. NeurIPS 2026Black-Box Inference of LLM Architectural Properties with Restrictive API Access
39. NeurIPS 2026Bottleneck Benchmark: Sequence Compression Under Controlled Difficulty and Fixed Latent Size
40. NeurIPS 2026Bridging Compute- and Data-Optimal Pretraining
41. NeurIPS 2026Budgeting Discretion: Theory and Evidence on Street-Level Decision-Making
42. NeurIPS 2026CalArena: A Large Scale Post-Hoc Calibration Benchmark
43. NeurIPS 2026CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents
44. NeurIPS 2026Castle-in-the-Air: Probing the Foundational Visual Deficits of MLLMs via Bottom-Up Cognitive Factors
45. NeurIPS 2026Causal Evaluation of Membership Inference Attacks
46. NeurIPS 2026Certified but Private: Scalable Zero-Knowledge Proofs for the Formal Verification of Neural Networks
47. NeurIPS 2026Chain-of-Thought Is Not Explainability
48. NeurIPS 2026Chatter Attack: Resource Consumption Attack for Large Language Models
49. NeurIPS 2026ChronosAlign: A Large-Scale, Updatable Benchmark for Decomposing Temporal Alignment in LLMs
50. NeurIPS 2026Classification at the Edge of Stability: Unifying Self-Stabilization and Convergence Rates

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。