视觉-语言-动作论文趋势 2023–2026

主要结论

• 视觉-语言-动作论文从 2023 年的 257 篇增长到 2026 年的 708 篇，三年间扩大到约 2.8 倍。
• CVPR 是发视觉-语言-动作论文最多的会议，2023–2026 年共 640 篇，占四个会议总量的 39%。
• 交叉方向里涨得最快的是应用 · computer vision：同时属于两个主题的论文从 2023 年的 21 篇增至 2026 年的 135 篇。
• 在「机器人与具身」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的人形控制是 3.8 倍，视觉-语言-动作是 2.8 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 Dual-Domain Vision Transformer with Spectral Positional Bias
• ICML 2026FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
• ICLR 2026Curvature-Guided Task Synergy for Skeleton based Temporal Action Segmentation
• CVPR 2026ActAvatar Temporally-Aware Precise Action Control for Talking Avatars
• NeurIPS 2025Doodle to Detect: A Goofy but Powerful Approach to Skeleton-based Hand Gesture Recognition
• ICML 2025Feasible Action Search for Bandit Linear Programs via Thompson Sampling
• ICLR 2025Action Sequence Augmentation for Action Anticipation
• CVPR 2025Active Event-based Stereo Vision
• NeurIPS 2024GAIA: Rethinking Action Quality Assessment for AI-Generated Videos
• ICML 2024Causal Action Influence Aware Counterfactual Data Augmentation
• ICLR 2024Matrix Manifold Neural Networks++
• CVPR 2024End-to-End Spatio-Temporal Action Localisation with Video Transformers
• NeurIPS 2023Activity Grammars for Temporal Action Segmentation
• ICML 2023Algorithmic Collective Action in Machine Learning
• ICLR 2023A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
• CVPR 20233Mformer: Multi-Order Multi-Mode Transformer for Skeletal Action Recognition
• NeurIPS 2026A Statistical Framework for Algorithmic Collective Action with Multiple Collectives
• ICML 2026From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
• ICLR 2026EAST: Early Action Prediction Sampling Strategy with Token Masking
• CVPR 2026DarkShake-DVS Event-based Human Action Recognition under Low-light and Shaking Camera

全部视觉-语言-动作论文

共 126 篇，第 3 / 3 页

101. ICML 2026SLAP: The Semantic Least Action Principle for Variational Video-Language Modeling
102. ICML 2026SPAR: Support-Preserving Action Rectification
103. ICML 2026Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
104. ICML 2026SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
105. ICML 2026Spectral Heat Flow for Conservative Token Condensation in Vision-Language Models
106. ICML 2026StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
107. ICML 2026Tabero: Learning Gentle Manipulation with Closed-Loop Force Feedback from Vision, Touch, and Language
108. ICML 2026Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
109. ICML 2026TGV-KV: Text-Grounded KV Eviction for Vision-Language Models
110. ICML 2026The Lie We Tell: Correcting the Euclidean Fallacy in Vision Language Action Policies via Score Matching on Tangent Space
111. ICML 2026TRAP: Hijacking VLA CoT-Reasoning via Adversarial Patches
112. ICML 2026UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing
113. ICML 2026Understanding Behavior Cloning with Action Quantization
114. ICML 2026Unlocking Noise-Resistant Vision: Key Architectural Secrets for Robust Models Against Gaussian Noise
115. ICML 2026VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
116. ICML 2026VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models
117. ICML 2026Vision Language Models Cannot Reason About Physical Transformation
118. ICML 2026Vision Transformer Finetuning Benefits from Non-Smooth Components
119. ICML 2026Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
120. ICML 2026Vision-Language-Action Pretraining from Large-Scale Human Videos
121. ICML 2026ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models
122. ICML 2026VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models
123. ICML 2026VLANeXt: Recipes for Building Strong VLA Models
124. ICML 2026VLM-RobustBench: A Comprehensive Benchmark for Robustness of Vision-Language Models
125. ICML 2026What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
126. ICML 2026XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations

常见问题

2023–2026 年四大会议一共有多少篇视觉-语言-动作论文？

共 1,639 篇，按年份分别是 2023 年 257 篇、2024 年 329 篇、2025 年 345 篇、2026 年 708 篇。

NeurIPS 2026 有多少篇视觉-语言-动作论文？

NeurIPS 2026 有 204 篇视觉-语言-动作论文，上一届是 108 篇。

ICLR 2026 有多少篇视觉-语言-动作论文？

ICLR 2026 有 113 篇视觉-语言-动作论文，上一届是 64 篇。

ICML 2026 有多少篇视觉-语言-动作论文？

ICML 2026 有 126 篇视觉-语言-动作论文，上一届是 33 篇。

CVPR 2026 有多少篇视觉-语言-动作论文？

CVPR 2026 有 265 篇视觉-语言-动作论文，上一届是 140 篇。

哪个会议的视觉-语言-动作论文最多？

CVPR，2023–2026 年共 640 篇。