逻辑与神经论文趋势 2023–2026

主要结论

• 逻辑与神经论文从 2023 年的 162 篇降到 2026 年的 86 篇，热度在回落。
• NeurIPS 是发逻辑与神经论文最多的会议，2023–2026 年共 173 篇，占四个会议总量的 47%。
• 交叉方向里涨得最快的是社会层面 · accountability transparency and interpretability：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 8 篇。
• 在「神经符号」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的数学推理是 10 倍，逻辑与神经是 0.5 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 2026B$^3$-PWL: GPU-Batched Branch-and-Bound for Piecewise-Linear Optimization with SOS2 Constraints
• ICML 2026Length Generalization Bounds for Transformers
• ICLR 2026From Neural Networks to Logical Theories: The Correspondence between Fibring Modal Logics and Fibring Neural Networks
• CVPR 2026Med-CMR A Fine-Grained Benchmark Integrating Visual Evidence and Clinical Logic
• NeurIPS 2025Characterizing the Expressivity of Fixed-Precision Transformer Language Models
• ICML 2025Counterfactual Graphical Models: Constraints and Inference
• ICLR 2025Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
• CVPR 2025Learning Affine Correspondences by Integrating Geometric Constraints
• NeurIPS 2024Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints
• ICML 2024A Field Guide for Pacing Budget and ROS Constraints
• ICLR 2024LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
• CVPR 2024MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints
• NeurIPS 2023Aligning Gradient and Hessian for Neural Signed Distance Function
• ICML 2023Eventual Discounting Temporal Logic Counterfactual Experience Replay
• ICLR 2023Global Explainability of GNNs via Logic Combination of Learned Concepts
• CVPR 2023Handy: Towards a High Fidelity 3D Hand Shape and Appearance Model
• NeurIPS 2026Batched Stochastic Linear Bandits with 1-Bit Communication Constraints
• ICML 2026KANFIS: A Neuro-Symbolic Framework for Interpretable and Uncertainty-Aware Learning
• ICLR 2026The Logical Expressiveness of Topological Neural Networks
• CVPR 2026NeuroRule Bridging Vision and Logic with Differentiable Rule Induction

全部逻辑与神经论文

共 112 篇，第 2 / 3 页

51. ICML 2024Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
52. ICML 2024Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
53. ICML 2024Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
54. ICML 2024Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks
55. ICML 2024Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints
56. ICML 2024Online Learning under Budget and ROI Constraints via Weak Adaptivity
57. ICML 2024Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations
58. ICML 2024Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
59. ICML 2024Representation Surgery: Theory and Practice of Affine Steering
60. ICML 2024Symmetry Induces Structure and Constraint of Learning
61. ICML 2024TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
62. ICML 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
63. ICML 2024Trustworthy Actionable Perturbations
64. ICML 2024Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
65. ICML 2024Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
66. ICML 2023A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
67. ICML 2023Achieving Hierarchy-Free Approximation for Bilevel Programs with Equilibrium Constraints
68. ICML 2023Alternately Optimized Graph Neural Networks
69. ICML 2023Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
70. ICML 2023BiBench: Benchmarking and Analyzing Network Binarization
71. ICML 2023Certified Robust Neural Networks: Generalization and Corruption Resistance
72. ICML 2023Controllable Neural Symbolic Regression
73. ICML 2023Distributed Linear Bandits under Communication Constraints
74. ICML 2023Does a Neural Network Really Encode Symbolic Concepts?
75. ICML 2023Effective Neural Topic Modeling with Embedding Clustering Regularization
76. ICML 2023Efficiently predicting high resolution mass spectra with graph neural networks
77. ICML 2023Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
78. ICML 2023Eventual Discounting Temporal Logic Counterfactual Experience Replay
79. ICML 2023Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks
80. ICML 2023Generalization on the Unseen, Logic Reasoning and Degree Curriculum
81. ICML 2023Generalizing Neural Wave Functions
82. ICML 2023Hierarchical Neural Coding for Controllable CAD Model Generation
83. ICML 2023Implicit Neural Spatial Representations for Time-dependent PDEs
84. ICML 2023Improving Graph Neural Networks with Learnable Propagation Operators
85. ICML 2023Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic
86. ICML 2023Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks
87. ICML 2023Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains
88. ICML 2023Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set
89. ICML 2023Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints
90. ICML 2023Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
91. ICML 2023Multi-channel Autobidding with Budget and ROI Constraints
92. ICML 2023Nearly Optimal Competitive Ratio for Online Allocation Problems with Two-sided Resource Constraints and Finite Requests
93. ICML 2023Neural signature kernels as infinite-width-depth-limits of controlled ResNets
94. ICML 2023NeuralSlice: Neural 3D Triangle Mesh Reconstruction via Slicing 4D Tetrahedral Meshes
95. ICML 2023Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks
96. ICML 2023On Regularization and Inference with Label Constraints
97. ICML 2023On the Expressive Power of Geometric Graph Neural Networks
98. ICML 2023On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization
99. ICML 2023On the Initialization of Graph Neural Networks
100. ICML 2023Online Nonstochastic Control with Adversarial and Static Constraints

常见问题

2023–2026 年四大会议一共有多少篇逻辑与神经论文？

共 366 篇，按年份分别是 2023 年 162 篇、2024 年 64 篇、2025 年 54 篇、2026 年 86 篇。

NeurIPS 2026 有多少篇逻辑与神经论文？

NeurIPS 2026 有 32 篇逻辑与神经论文，上一届是 23 篇。

ICLR 2026 有多少篇逻辑与神经论文？

ICLR 2026 有 20 篇逻辑与神经论文，上一届是 11 篇。

ICML 2026 有多少篇逻辑与神经论文？

ICML 2026 有 25 篇逻辑与神经论文，上一届是 12 篇。

CVPR 2026 有多少篇逻辑与神经论文？

CVPR 2026 有 9 篇逻辑与神经论文，上一届是 8 篇。

哪个会议的逻辑与神经论文最多？

NeurIPS，2023–2026 年共 173 篇。