可微推理论文趋势 2023–2026

主要结论

• 可微推理论文从 2023 年的 31 篇增长到 2026 年的 79 篇，三年间扩大到约 2.5 倍。
• NeurIPS 是发可微推理论文最多的会议，2023–2026 年共 65 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是数学推理：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 29 篇。
• 在「神经符号」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的数学推理是 10 倍，可微推理是 2.5 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 2026Beyond MSE: Differentiable Complexity Priors for Structure-Preserving Neural Denoising
• ICML 2026Differentiable Conformal Training for LLM Reasoning Factuality
• ICLR 2026$\boldsymbol{\partial^\infty}$-Grid: A Neural Differential Equation Solver with Differentiable Feature Grids
• CVPR 2026D-Convexity A Unified Differentiable Convex Shape Prior via Quasi-Concavity for
• NeurIPS 2025Consistency Conditions for Differentiable Surrogate Losses
• ICML 2025DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
• ICLR 2025Analytic DAG Constraints for Differentiable DAG Learning
• CVPR 2025Differentiable Inverse Rendering with Interpretable Basis BRDFs
• NeurIPS 2024DeiSAM: Segment Anything with Deictic Prompting
• ICML 2024A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
• ICLR 2024Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
• CVPR 2024Differentiable Display Photometric Stereo
• NeurIPS 2023Differentiable Clustering with Perturbed Spanning Forests
• ICML 2023End-to-end Differentiable Clustering with Associative Memories
• ICLR 2023Learning Group Importance using the Differentiable Hypergeometric Distribution
• CVPR 2023Deep Learning of Partial Graph Matching via Differentiable Top-K
• NeurIPS 2026Differentiable Exact Learning of Algorithms
• ICML 2026Hide&Seek: Learning to Explain in an End-to-End Differentiable Network
• ICLR 2026Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity
• CVPR 2026DiffBMP Differentiable Rendering with Bitmap Primitives

全部可微推理论文

共 31 篇，第 1 / 1 页

1. CVPR 2023Deep Learning of Partial Graph Matching via Differentiable Top-K
2. CVPR 2023Differentiable Architecture Search With Random Features
3. CVPR 2023Differentiable Shadow Mapping for Efficient Inverse Graphics
4. CVPR 2023Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares
5. CVPR 2023Plateau-Reduced Differentiable Path Tracing
6. CVPR 2023TMO: Textured Mesh Acquisition of Objects With a Mobile Device by Using Differentiable Rendering
7. ICLR 2023Can Neural Networks Learn Implicit Logic from Physical Reasoning?
8. ICLR 2023DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline
9. ICLR 2023Improving Differentiable Neural Architecture Search by Encouraging Transferability
10. ICLR 2023Learning Group Importance using the Differentiable Hypergeometric Distribution
11. ICLR 2023Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
12. ICLR 2023Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
13. ICLR 2023Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
14. ICLR 2023TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
15. ICLR 2023VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis
16. ICLR 2023Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic
17. ICML 2023Differentiable Tree Operations Promote Compositional Generalization
18. ICML 2023End-to-end Differentiable Clustering with Associative Memories
19. ICML 2023Interpretable Neural-Symbolic Concept Reasoning
20. ICML 2023Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic
21. ICML 2023Neural Status Registers
22. NeurIPS 2023Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives
23. NeurIPS 2023Differentiable Clustering with Perturbed Spanning Forests
24. NeurIPS 2023Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs
25. NeurIPS 2023Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
26. NeurIPS 2023Learning Reliable Logical Rules with SATNet
27. NeurIPS 2023Operation-Level Early Stopping for Robustifying Differentiable NAS
28. NeurIPS 2023PDP: Parameter-free Differentiable Pruning is All You Need
29. NeurIPS 2023TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph
30. NeurIPS 2023What’s Left? Concept Grounding with Logic-Enhanced Foundation Models
31. NeurIPS 2023Why think step by step? Reasoning emerges from the locality of experience

常见问题

2023–2026 年四大会议一共有多少篇可微推理论文？

共 185 篇，按年份分别是 2023 年 31 篇、2024 年 29 篇、2025 年 46 篇、2026 年 79 篇。

NeurIPS 2026 有多少篇可微推理论文？

NeurIPS 2026 有 28 篇可微推理论文，上一届是 22 篇。

ICLR 2026 有多少篇可微推理论文？

ICLR 2026 有 16 篇可微推理论文，上一届是 13 篇。

ICML 2026 有多少篇可微推理论文？

ICML 2026 有 14 篇可微推理论文，上一届是 5 篇。

CVPR 2026 有多少篇可微推理论文？

CVPR 2026 有 21 篇可微推理论文，上一届是 6 篇。

哪个会议的可微推理论文最多？

NeurIPS，2023–2026 年共 65 篇。