推理模型论文趋势 2023–2026

主要结论

• 推理模型论文从 2023 年的 470 篇增长到 2026 年的 1,799 篇，三年间扩大到约 3.8 倍。
• NeurIPS 是发推理模型论文最多的会议，2023–2026 年共 1,253 篇，占四个会议总量的 36%。
• 交叉方向里涨得最快的是强化学习：同时属于两个主题的论文从 2023 年的 9 篇增至 2026 年的 437 篇。
• 在「前沿系统」的 4 个主题里，它的 2026 年论文数排第 3；同组增长最快的AI 智能体是 12 倍，推理模型是 3.8 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 Mechanistic Analysis of Looped Reasoning Language Models
• ICML 2026A Formal Comparison Between Chain of Thought and Latent Thought
• ICLR 2026A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models
• CVPR 2026Asking like Socrates Socrates helps VLMs understand remote sensing images
• NeurIPS 2025A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1
• ICML 2025A Reasoning-Based Approach to Cryptic Crossword Clue Solving
• ICLR 2025A Formal Framework for Understanding Length Generalization in Transformers
• CVPR 2025Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought
• NeurIPS 2024Are Large Language Models Good Statisticians?
• ICML 2024Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
• ICLR 2024Amortizing intractable inference in large language models
• CVPR 2024Generate Subgoal Images before Act: Unlocking the Chain-of-Thought Reasoning in Diffusion Model for Robot Manipulation with Multimodal Prompts
• NeurIPS 2023A benchmark of categorical encoders for binary classification
• ICML 2023Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
• ICLR 2023Automatic Chain of Thought Prompting in Large Language Models
• CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
• NeurIPS 2026A Solvable Model of Chain-of-Thought in In-Context Learning
• ICML 2026A Narrowing Geometry in Contaminated Reasoning
• ICLR 2026A State-Transition Framework for Efficient LLM Reasoning
• CVPR 2026Beyond Weak Supervision MLLMs-Guided Graded Knowledge Distillation for Unsupervised Camouflaged

全部推理模型论文

共 913 篇，第 17 / 19 页

801. ICML 2024Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
802. ICML 2024Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
803. ICML 2024Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
804. ICML 2024What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks
805. ICML 2023A Statistical Perspective on Retrieval-Based Models
806. ICML 2023A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs
807. ICML 2023A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates
808. ICML 2023AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
809. ICML 2023Adaptive Computation with Elastic Input Sequence
810. ICML 2023An Effective Meaningful Way to Evaluate Survival Models
811. ICML 2023Bag of Tricks for Training Data Extraction from Language Models
812. ICML 2023Bandits with Knapsacks: Advice on Time-Varying Demands
813. ICML 2023Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models
814. ICML 2023Benign Overfitting in Deep Neural Networks under Lazy Training
815. ICML 2023Benign Overfitting in Two-layer ReLU Convolutional Neural Networks
816. ICML 2023Beyond the Edge of Stability via Two-step Gradient Updates
817. ICML 2023Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
818. ICML 2023CLIPood: Generalizing CLIP to Out-of-Distributions
819. ICML 2023Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator
820. ICML 2023Consistency Models
821. ICML 2023Constraint Reasoning Embedded Structured Prediction
822. ICML 2023Contextual Reliability: When Different Features Matter in Different Contexts
823. ICML 2023Continuously Parameterized Mixture Models
824. ICML 2023Convex Geometry of ReLU-layers, Injectivity on the Ball and Local Reconstruction
825. ICML 2023Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders
826. ICML 2023Counterfactual Identifiability of Bijective Causal Models
827. ICML 2023Data Feedback Loops: Model-driven Amplification of Dataset Biases
828. ICML 2023Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation
829. ICML 2023Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?
830. ICML 2023Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions
831. ICML 2023Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat
832. ICML 2023Do Perceptually Aligned Gradients Imply Robustness?
833. ICML 2023Emergent Agentic Transformer from Chain of Hindsight Experience
834. ICML 2023Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions
835. ICML 2023Explaining the effects of non-convergent MCMC in the training of Energy-Based Models
836. ICML 2023Exploiting locality in high-dimensional Factorial hidden Markov models
837. ICML 2023Fast Rates in Time-Varying Strongly Monotone Games
838. ICML 2023Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
839. ICML 2023Formalizing Preferences Over Runtime Distributions
840. ICML 2023Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
841. ICML 2023Generalization on the Unseen, Logic Reasoning and Degree Curriculum
842. ICML 2023Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization
843. ICML 2023Graphically Structured Diffusion Models
844. ICML 2023High Fidelity Image Counterfactuals with Probabilistic Causal Models
845. ICML 2023Hyena Hierarchy: Towards Larger Convolutional Language Models
846. ICML 2023Identifiability of Label Noise Transition Matrix
847. ICML 2023Implicit Neural Spatial Representations for Time-dependent PDEs
848. ICML 2023Inferring Relational Potentials in Interacting Systems
849. ICML 2023Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning
850. ICML 2023Input Perturbation Reduces Exposure Bias in Diffusion Models

常见问题

2023–2026 年四大会议一共有多少篇推理模型论文？

共 3,512 篇，按年份分别是 2023 年 470 篇、2024 年 311 篇、2025 年 932 篇、2026 年 1,799 篇。

NeurIPS 2026 有多少篇推理模型论文？

NeurIPS 2026 有 361 篇推理模型论文，上一届是 500 篇。

ICLR 2026 有多少篇推理模型论文？

ICLR 2026 有 652 篇推理模型论文，上一届是 203 篇。

ICML 2026 有多少篇推理模型论文？

ICML 2026 有 582 篇推理模型论文，上一届是 159 篇。

CVPR 2026 有多少篇推理模型论文？

CVPR 2026 有 204 篇推理模型论文，上一届是 70 篇。

哪个会议的推理模型论文最多？

NeurIPS，2023–2026 年共 1,253 篇。