上下文压缩论文趋势 2023–2026

主要结论

• 上下文压缩论文从 2023 年的 39 篇增长到 2026 年的 136 篇，三年间扩大到约 3.5 倍。
• NeurIPS 是发上下文压缩论文最多的会议，2023–2026 年共 123 篇，占四个会议总量的 34%。
• 交叉方向里涨得最快的是深度学习 · large language models：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 13 篇。
• 在「长上下文与记忆」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的检索记忆是 6.6 倍，上下文压缩是 3.5 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 2026A Free Lunch in LLM Compression: Revisiting Retraining after Pruning
• ICML 2026A Unified Sparse Attention via Multi-Granularity Compression
• ICLR 2026An evolutionary perspective on modes of learning in Transformers
• CVPR 2026AstraNav-Memory Contexts Compression for Long Memory
• NeurIPS 2025AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
• ICML 2025Does learning the right latent variables necessarily improve in-context learning?
• ICLR 2025Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
• CVPR 2025ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression
• NeurIPS 2024StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
• ICML 2024Agnostic Sample Compression Schemes for Regression
• ICLR 2024Compressed Context Memory for Online Language Model Interaction
• CVPR 2024Diversity-aware Channel Pruning for StyleGAN Compression
• NeurIPS 2023Do Not Marginalize Mechanisms, Rather Consolidate!
• ICML 2023Private Federated Learning with Autotuned Compression
• ICLR 2023$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
• CVPR 2023AutoAD: Movie Description in Context
• NeurIPS 2026A Self-Evolving Framework for Efficient Terminal Agents via Observational Context Compression
• ICML 2026Context-Driven Incremental Compression for Multi-Turn Dialogue Generation
• ICLR 2026Autoencoding-Free Context Compression for LLMs via Contextual Semantic Anchors
• CVPR 2026Featurising Pixels from Dynamic 3D Scenes with Linear In-Context Learners

全部上下文压缩论文

共 20 篇，第 1 / 1 页

1. ICML 2025CommVQ: Commutative Vector Quantization for KV Cache Compression
2. ICML 2025Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
3. ICML 2025DLP: Dynamic Layerwise Pruning in Large Language Models
4. ICML 2025Does learning the right latent variables necessarily improve in-context learning?
5. ICML 2025Efficient LiDAR Reflectance Compression via Scanning Serialization
6. ICML 2025Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
7. ICML 2025EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
8. ICML 2025In-Context Deep Learning via Transformer Models
9. ICML 2025In-Context Learning and Occam's Razor
10. ICML 2025Iterative Vectors: In-Context Gradient Steering without Backpropagation
11. ICML 2025Learning In-context $n$-grams with Transformers: Sub-$n$-grams Are Near-Stationary Points
12. ICML 2025Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries
13. ICML 2025NExtLong: Toward Effective Long-Context Training without Long Documents
14. ICML 2025ParallelComp: Parallel Long-Context Compressor for Length Extrapolation
15. ICML 2025Prompt-based Depth Pruning of Large Language Models
16. ICML 2025Retraining-free Merging of Sparse MoE via Hierarchical Clustering
17. ICML 2025RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
18. ICML 2025SkipGPT: Each Token is One of a Kind
19. ICML 2025Training Dynamics of In-Context Learning in Linear Attention
20. ICML 2025Weight matrices compression based on PDB model in deep neural networks

常见问题

2023–2026 年四大会议一共有多少篇上下文压缩论文？

共 365 篇，按年份分别是 2023 年 39 篇、2024 年 81 篇、2025 年 109 篇、2026 年 136 篇。

NeurIPS 2026 有多少篇上下文压缩论文？

NeurIPS 2026 有 50 篇上下文压缩论文，上一届是 38 篇。

ICLR 2026 有多少篇上下文压缩论文？

ICLR 2026 有 28 篇上下文压缩论文，上一届是 32 篇。

ICML 2026 有多少篇上下文压缩论文？

ICML 2026 有 39 篇上下文压缩论文，上一届是 20 篇。

CVPR 2026 有多少篇上下文压缩论文？

CVPR 2026 有 19 篇上下文压缩论文，上一届是 19 篇。

哪个会议的上下文压缩论文最多？

NeurIPS，2023–2026 年共 123 篇。