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 19 / 26 页

901. NeurIPS 2025Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
902. NeurIPS 2025Unextractable Protocol Models: Collaborative Training and Inference without Weight Materialization
903. NeurIPS 2025Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning
904. NeurIPS 2025Unifying Proportional Fairness in Centroid and Non-Centroid Clustering
905. NeurIPS 2025Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
906. NeurIPS 2025UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
907. NeurIPS 2025Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
908. NeurIPS 2025Unlearning-Aware Minimization
909. NeurIPS 2025Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing
910. NeurIPS 2025Unveiling Concept Attribution in Diffusion Models
911. NeurIPS 2025Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization
912. NeurIPS 2025Unveiling the Uncertainty in Embodied and Operational Carbon of Large AI Models through a Probabilistic Carbon Accounting Model
913. NeurIPS 2025Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs
914. NeurIPS 2025V-CECE: Visual Counterfactual Explanations via Conceptual Edits
915. NeurIPS 2025Vector Database Watermarking
916. NeurIPS 2025Versatile Transferable Unlearnable Example Generator
917. NeurIPS 2025Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
918. NeurIPS 2025Vision Transformers Don't Need Trained Registers
919. NeurIPS 2025VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set
920. NeurIPS 2025Volume Transmission Implements Context Factorization to Target Online Credit Assignment and Enable Compositional Generalization
921. NeurIPS 2025WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks
922. NeurIPS 2025Watermarking Autoregressive Image Generation
923. NeurIPS 2025What Happens During the Loss Plateau? Understanding Abrupt Learning in Transformers
924. NeurIPS 2025What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
925. NeurIPS 2025What Moves the Eyes: Doubling Mechanistic Model Performance Using Deep Networks to Discover and Test Cognitive Hypotheses
926. NeurIPS 2025What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
927. NeurIPS 2025What Really is a Member? Discrediting Membership Inference via Poisoning
928. NeurIPS 2025When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
929. NeurIPS 2025When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration
930. NeurIPS 2025Who You Are Matters: Bridging Interests and Social Roles via LLM-Enhanced Logic Recommendation
931. NeurIPS 2025Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations
932. NeurIPS 2025Why Do Some Language Models Fake Alignment While Others Don't?
933. NeurIPS 2025Wisdom is Knowing What not to Say: Hallucination-Free LLMs Unlearning via Attention Shifting
934. NeurIPS 2025WMCopier: Forging Invisible Watermarks on Arbitrary Images
935. NeurIPS 2025World Models Should Prioritize the Unification of Physical and Social Dynamics
936. NeurIPS 2025You Only Communicate Once: One-shot Federated Low-Rank Adaptation of MLLM
937. NeurIPS 2025Zero-Shot Detection of LLM-Generated Text via Implicit Reward Model
938. NeurIPS 2025Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
939. NeurIPS 20242D-OOB: Attributing Data Contribution Through Joint Valuation Framework
940. NeurIPS 20243-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
941. NeurIPS 2024A Concept-Based Explainability Framework for Large Multimodal Models
942. NeurIPS 2024A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
943. NeurIPS 2024A Functional Extension of Semi-Structured Networks
944. NeurIPS 2024A hierarchical decomposition for explaining ML performance discrepancies
945. NeurIPS 2024A Polar coordinate system represents syntax in large language models
946. NeurIPS 2024A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
947. NeurIPS 2024A Systematic Review of NeurIPS Dataset Management Practices
948. NeurIPS 2024A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
949. NeurIPS 2024A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
950. NeurIPS 2024Abrupt Learning in Transformers: A Case Study on Matrix Completion

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。