特征归因论文趋势 2023–2026
Saliency 与 SHAP
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 695 篇被归入该主题的论文。
主要结论
- 特征归因论文从 2023 年的 118 篇增长到 2026 年的 219 篇,三年间扩大到约 1.9 倍。
- NeurIPS 是发特征归因论文最多的会议,2023–2026 年共 193 篇,占四个会议总量的 28%。
- 交叉方向里涨得最快的是理论 · learning theory:同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 14 篇。
- 在「可解释性」的 5 个主题里,它的 2026 年论文数排第 1;同组增长最快的机制解释是 8.1 倍,特征归因是 1.9 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 25 | 29 | 21 | 43 | 118 |
| 2024 | 50 | 36 | 47 | 35 | 168 |
| 2025 | 57 | 42 | 51 | 40 | 190 |
| 2026 | 61 | 53 | 56 | 49 | 219 |
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 2026ADAPT: Hybrid Prompt Optimization for LLM Feature Visualization
- ICML 2026Activation with Intrinsic-Extrinsic Consensus
- ICLR 2026AnyUp: Universal Feature Upsampling
- CVPR 2026A Training-Free Style-Personalization via SVD-Based Feature Decomposition
- NeurIPS 2025Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks
- ICML 2025BCE vs. CE in Deep Feature Learning
- ICLR 2025A Differentiable Rank-Based Objective for Better Feature Learning
- CVPR 2025A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
- NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
- ICML 2024Asymptotics of feature learning in two-layer networks after one gradient-step
- ICLR 2024An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
- CVPR 2024DYSON: Dynamic Feature Space Self-Organization for Online Task-Free Class Incremental Learning
- NeurIPS 2023$\mathcal{M}^4$: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models
- ICML 2023Decoding Layer Saliency in Language Transformers
- ICLR 2023Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN?
- CVPR 2023A Practical Upper Bound for the Worst-Case Attribution Deviations
- NeurIPS 2026Adaptive Feature Propagation for Attribute-Missing Graph Clustering
- ICML 2026Aggregate Models, Not Explanations: Improving Feature Importance Estimation
- ICLR 2026Attribution-Guided Decoding
- CVPR 2026FBTA Enabling Single-GPU End-to-End Gigapixel WSI Classification with Feature Bridging
全部特征归因论文
共 42 篇,第 1 / 1 页
- ICLR 2025A Differentiable Rank-Based Objective for Better Feature Learning
- ICLR 2025Accelerating Diffusion Transformers with Token-wise Feature Caching
- ICLR 2025AI as Humanity’s Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text
- ICLR 2025AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution
- ICLR 2025Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
- ICLR 2025Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator
- ICLR 2025Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
- ICLR 2025Capturing the Temporal Dependence of Training Data Influence
- ICLR 2025Deep Networks Learn Features From Local Discontinuities in the Label Function
- ICLR 2025DICE: Data Influence Cascade in Decentralized Learning
- ICLR 2025Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
- ICLR 2025Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons
- ICLR 2025Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
- ICLR 2025Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse
- ICLR 2025Feature-Based Online Bilateral Trade
- ICLR 2025For Better or For Worse? Learning Minimum Variance Features With Label Augmentation
- ICLR 2025Formation of Representations in Neural Networks
- ICLR 2025GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring
- ICLR 2025Graph Neural Ricci Flow: Evolving Feature from a Curvature Perspective
- ICLR 2025How Feature Learning Can Improve Neural Scaling Laws
- ICLR 2025Influence Functions for Scalable Data Attribution in Diffusion Models
- ICLR 2025InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
- ICLR 2025Joint Graph Rewiring and Feature Denoising via Spectral Resonance
- ICLR 2025Learning Hierarchical Polynomials of Multiple Nonlinear Features
- ICLR 2025Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
- ICLR 2025LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
- ICLR 2025Machine Unlearning via Simulated Oracle Matching
- ICLR 2025Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
- ICLR 2025MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
- ICLR 2025On the Feature Learning in Diffusion Models
- ICLR 2025Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
- ICLR 2025RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
- ICLR 2025Rethinking Multiple-Instance Learning From Feature Space to Probability Space
- ICLR 2025Rethinking Shapley Value for Negative Interactions in Non-convex Games
- ICLR 2025Robust Feature Learning for Multi-Index Models in High Dimensions
- ICLR 2025Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification
- ICLR 2025Scalable Influence and Fact Tracing for Large Language Model Pretraining
- ICLR 2025Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale
- ICLR 2025Three Mechanisms of Feature Learning in a Linear Network
- ICLR 2025Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
- ICLR 2025Unlearning-based Neural Interpretations
- ICLR 2025When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查特征归因在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "feature-attribution"}
常见问题
- 2023–2026 年四大会议一共有多少篇特征归因论文?
- 共 695 篇,按年份分别是 2023 年 118 篇、2024 年 168 篇、2025 年 190 篇、2026 年 219 篇。
- NeurIPS 2026 有多少篇特征归因论文?
- NeurIPS 2026 有 61 篇特征归因论文,上一届是 57 篇。
- ICLR 2026 有多少篇特征归因论文?
- ICLR 2026 有 53 篇特征归因论文,上一届是 42 篇。
- ICML 2026 有多少篇特征归因论文?
- ICML 2026 有 56 篇特征归因论文,上一届是 51 篇。
- CVPR 2026 有多少篇特征归因论文?
- CVPR 2026 有 49 篇特征归因论文,上一届是 40 篇。
- 哪个会议的特征归因论文最多?
- NeurIPS,2023–2026 年共 193 篇。