PDF 理解论文趋势 2023–2026
长文档理解
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 102 篇被归入该主题的论文。
主要结论
- PDF 理解论文从 2023 年的 6 篇增长到 2026 年的 39 篇，三年间扩大到约 6.5 倍。
- CVPR 是发PDF 理解论文最多的会议，2023–2026 年共 39 篇，占四个会议总量的 38%。
- 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 17 篇。
- 在「文档与版式」的 5 个主题里，它的 2026 年论文数排第 1。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 1 | 1 | 0 | 4 | 6 |
| 2024 | 7 | 4 | 4 | 7 | 22 |
| 2025 | 6 | 8 | 3 | 18 | 35 |
| 2026 | 21 | 6 | 2 | 10 | 39 |
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 2026DocScope: Benchmarking Verifiable Reasoning for Trustworthy Long-Document Understanding
- ICML 2026Explainable Forensics of Manipulated Segments in Untrimmed Long Videos
- ICLR 2026Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Understanding
- CVPR 2026MS-Temba Multi-Scale Temporal Mamba for Understanding Long Untrimmed Videos
- NeurIPS 2025Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks
- ICML 2025Position: Deep Learning is Not So Mysterious or Different
- ICLR 2025Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution
- CVPR 2025Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images
- NeurIPS 2024SRFUND: A Multi-Granularity Hierarchical Structure Reconstruction Benchmark in Form Understanding
- ICML 2024Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features
- ICLR 2024Nougat: Neural Optical Understanding for Academic Documents
- CVPR 2024Action Scene Graphs for Long-Form Understanding of Egocentric Videos
- NeurIPS 2023Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
- ICLR 2023Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
- CVPR 2023Long Range Pooling for 3D Large-Scale Scene Understanding
- NeurIPS 2026Towards Understanding Momentum Acceleration in River-Valley Loss Landscape
- ICML 2026SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States
- ICLR 2026Understanding the Learning Phases in Self-Supervised Learning via Critical Periods
- CVPR 2026Understanding Accelerating and Improving MeanFlow Training
- NeurIPS 2025PaceLLM: Brain-Inspired Large Language Models for Long-Context Understanding
全部PDF 理解论文
共 19 篇，第 1 / 1 页
- ICLR 2026LH-DECEPTION: Simulating and Understanding LLM Deceptive Behaviors in Long-Horizon Interactions
- ICLR 2026PRISMM-Bench: A Benchmark of Peer-Review Grounded Multimodal Inconsistencies
- ICLR 2026Revisiting Long-context Modeling from Context Denoising Perspective
- ICLR 2026Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Understanding
- ICLR 2026SURGE: Surprise-Guided Token Reduction for Efficient Video Understanding with VLMs
- ICLR 2026Understanding the Learning Phases in Self-Supervised Learning via Critical Periods
- ICLR 2025Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding
- ICLR 2025Enhancing Document Understanding with Group Position Embedding: A Novel Approach to Incorporate Layout Information
- ICLR 2025LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement
- ICLR 2025mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models
- ICLR 2025Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution
- ICLR 2025SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
- ICLR 2025SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
- ICLR 2025TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning
- ICLR 2024ADOPD: A Large-Scale Document Page Decomposition Dataset
- ICLR 2024Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding
- ICLR 2024Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs
- ICLR 2024Nougat: Neural Optical Understanding for Academic Documents
- ICLR 2023Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
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PDF 理解在 CVPR 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": "pdf-understanding"}
常见问题
- 2023–2026 年四大会议一共有多少篇PDF 理解论文？
- 共 102 篇，按年份分别是 2023 年 6 篇、2024 年 22 篇、2025 年 35 篇、2026 年 39 篇。
- NeurIPS 2026 有多少篇PDF 理解论文？
- NeurIPS 2026 有 21 篇PDF 理解论文，上一届是 6 篇。
- ICLR 2026 有多少篇PDF 理解论文？
- ICLR 2026 有 6 篇PDF 理解论文，上一届是 8 篇。
- ICML 2026 有多少篇PDF 理解论文？
- ICML 2026 有 2 篇PDF 理解论文，上一届是 3 篇。
- CVPR 2026 有多少篇PDF 理解论文？
- CVPR 2026 有 10 篇PDF 理解论文，上一届是 18 篇。
- 哪个会议的PDF 理解论文最多？
- CVPR，2023–2026 年共 39 篇。