多模态大模型论文趋势 2023–2026
视觉语言模型、图像/视频理解与生成式多模态基础模型
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 11,209 篇被归入该主题的论文。
主要结论
- 多模态大模型论文从 2023 年的 1,226 篇增长到 2026 年的 5,192 篇，三年间扩大到约 4.2 倍。
- NeurIPS 是发多模态大模型论文最多的会议，2023–2026 年共 3,319 篇，占四个会议总量的 30%。
- 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 35 篇增至 2026 年的 596 篇。
- 在「前沿系统」的 4 个主题里，它的 2026 年论文数排第 1；同组增长最快的AI 智能体是 12 倍，多模态大模型是 4.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 433 | 138 | 146 | 509 | 1,226 |
| 2024 | 446 | 321 | 323 | 626 | 1,716 |
| 2025 | 1,074 | 816 | 390 | 795 | 3,075 |
| 2026 | 1,366 | 1,401 | 1,051 | 1,374 | 5,192 |
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 2026$\text{A}^3$-VLA: Automatic Perception-Guided Attention Alignment for Robot Manipulation
- ICML 2026[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation
- ICLR 2026A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic
- CVPR 20263D Space as a Scratchpad for Editable Text-to-Image Generation
- NeurIPS 2025$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
- ICML 2025Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
- ICLR 2025$\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
- CVPR 20252DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image Classification
- NeurIPS 2024A Concept-Based Explainability Framework for Large Multimodal Models
- ICML 2024A Multimodal Automated Interpretability Agent
- ICLR 2024Alt-Text with Context: Improving Accessibility for Images on Twitter
- CVPR 2024Data-Efficient Multimodal Fusion on a Single GPU
- NeurIPS 20234M: Massively Multimodal Masked Modeling
- ICML 2023$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation
- ICLR 2023A Primal-Dual Framework for Transformers and Neural Networks
- CVPR 20233D Concept Learning and Reasoning From Multi-View Images
- NeurIPS 2026$\texttt{bispectrum}$: Selective $G$-Bispectra Made Practical
- ICML 2026$G^2$-Reader: Dual Evolving Graphs for Multimodal Document QA
- ICLR 2026A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
- CVPR 20263D-IDE 3D Implicit Depth Emergent
全部多模态大模型论文
共 2,676 篇，第 6 / 54 页
- ICLR 2026DeepEyesV2: Toward Agentic Multimodal Model
- ICLR 2026DeepScientist: Advancing Frontier-Pushing Scientific Findings Progressively
- ICLR 2026DeLeaker: Dynamic Inference-Time Reweighting For Semantic Leakage Mitigation in Text-to-Image Models
- ICLR 2026DeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining
- ICLR 2026Delving into Spectral Clustering with Vision-Language Representations
- ICLR 2026Demystifying Robot Diffusion Policies: Action Memorization and a Simple Lookup Table Alternative
- ICLR 2026Demystifying Supervision Data Generalization in Multimodal LMs
- ICLR 2026Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks
- ICLR 2026DepthLM: Metric Depth from Vision Language Models
- ICLR 2026DES-LOC: Desynced Low Communication Adaptive Optimizers for Foundation Models
- ICLR 2026DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning
- ICLR 2026Designing Affine-Invariant Neural Networks for Photometric Corruption Robustness and Generalization
- ICLR 2026Detecting Data Contamination in LLMs via In-Context Learning
- ICLR 2026Detecting Misbehaviors of Large Vision-Language Models by Evidential Uncertainty Quantification
- ICLR 2026Detecting Temporal Misalignment Attacks in Multimodal Fusion for Autonomous Driving
- ICLR 2026DiaBlo: Diagonal Blocks Are Sufficient For Finetuning
- ICLR 2026Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning
- ICLR 2026DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference
- ICLR 2026Differential Fine-Tuning Large Language Models Towards Better Diverse Reasoning Abilities
- ICLR 2026Difficulty–Diversity Collaborative Filtering for Data-Efficient LLM Fine-Tuning
- ICLR 2026Discern Truth from Falsehood: Reducing Over-Refusal via Contrastive Refinement
- ICLR 2026Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving
- ICLR 2026Discrete Latent Features Ablate Adversarial Attack: A Robust Prompt Tuning Framework for VLMs
- ICLR 2026Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining
- ICLR 2026Disentanglement of Variations with Multimodal Generative Modeling
- ICLR 2026Disentangling Knowledge Representations for Large Language Model Editing
- ICLR 2026Disrupting Hierarchical Reasoning: Adversarial Protection for Geographic Privacy in Multimodal Reasoning Models
- ICLR 2026Distilling the Thought, Watermarking the Answer: A Principle Semantic Guided Watermark for Reasoning Large Language Models
- ICLR 2026Distilling to Hybrid Attention Models via KL-Guided Layer Selection
- ICLR 2026Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models
- ICLR 2026Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence
- ICLR 2026DIVA-GRPO: Enhancing Multimodal Reasoning through Difficulty-Adaptive Variant Advantage
- ICLR 2026DiVE-k: DIFFERENTIAL VISUAL REASONING FOR FINE-GRAINED IMAGE RECOGNITION
- ICLR 2026Diversity-Incentivized Exploration for Versatile Reasoning
- ICLR 2026Divid: Disentangled Spatial-Temporal Modeling within LLMs for Temporally Grounded Video Understanding
- ICLR 2026Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models
- ICLR 2026DMAP: A Distribution Map for Text
- ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
- ICLR 2026Do 3D Large Language Models Really Understand 3D Spatial Relationships?
- ICLR 2026Do LLMs Forget What They Should? Evaluating In-Context Forgetting in Large Language Models
- ICLR 2026Do Vision-Language Models Respect Contextual Integrity in Location Disclosure?
- ICLR 2026Don’t Pass@$k$: A Bayesian Framework for Large Language Model Evaluation
- ICLR 2026Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search
- ICLR 2026Don't Throw Away Your Pretrained Model
- ICLR 2026DP-Fusion: Token-Level Differentially Private Inference for Large Language Models
- ICLR 2026DPad: Efficient Diffusion Language Models with Suffix Dropout
- ICLR 2026Dr.LLM: Dynamic Layer Routing in LLMs
- ICLR 2026Draft-based Approximate Inference for LLMs
- ICLR 2026Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing
- ICLR 2026DRBench: A Realistic Benchmark for Enterprise Deep Research
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 查多模态大模型在 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": "multimodal-llms"}
常见问题
- 2023–2026 年四大会议一共有多少篇多模态大模型论文？
- 共 11,209 篇，按年份分别是 2023 年 1,226 篇、2024 年 1,716 篇、2025 年 3,075 篇、2026 年 5,192 篇。
- NeurIPS 2026 有多少篇多模态大模型论文？
- NeurIPS 2026 有 1,366 篇多模态大模型论文，上一届是 1,074 篇。
- ICLR 2026 有多少篇多模态大模型论文？
- ICLR 2026 有 1,401 篇多模态大模型论文，上一届是 816 篇。
- ICML 2026 有多少篇多模态大模型论文？
- ICML 2026 有 1,051 篇多模态大模型论文，上一届是 390 篇。
- CVPR 2026 有多少篇多模态大模型论文？
- CVPR 2026 有 1,374 篇多模态大模型论文，上一届是 795 篇。
- 哪个会议的多模态大模型论文最多？
- NeurIPS，2023–2026 年共 3,319 篇。