Context Compression papers, 2023–2026

Key findings

• Context Compression went from 39 papers in 2023 to 136 in 2026, roughly 3.5x in three years.
• NeurIPS publishes the most Context Compression work: 123 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Deep learning · large language models: papers tagged with both rose from 1 in 2023 to 13 in 2026.
• Among the 5 topics under Long Context and Memory, it ranks #4 by 2026 paper count; the fastest grower in the group, Retrieval Memory, is up 6.6x versus 3.5x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Context Compression papers

50 papers, page 1 of 1

1. NeurIPS 2026A Free Lunch in LLM Compression: Revisiting Retraining after Pruning
2. NeurIPS 2026A Self-Evolving Framework for Efficient Terminal Agents via Observational Context Compression
3. NeurIPS 2026Accelerating Long-Context LLM Prefill via Layer-wise Progressive Token Pruning in Local Deployment
4. NeurIPS 2026Adaptive Mass-Segmented KV Compression for Long-Context Reasoning
5. NeurIPS 2026Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics
6. NeurIPS 2026Bayes-Sufficient Compression Is Not Enough: How Communication Helps in Multi-Agent Systems?
7. NeurIPS 2026Can In-Context Learning Support Intrinsic Curiosity?
8. NeurIPS 2026Can Language Models Actually Retrieve In-Context? Drowning in Documents at Million Token Scale
9. NeurIPS 2026Clapping: Removing Per-sample Storage for Pipeline Parallel Learning with Communication Compression
10. NeurIPS 2026COMPOT: Calibration-Optimized Matrix Procrustes Orthogonalization for Transformers Compression
11. NeurIPS 2026CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching
12. NeurIPS 2026CutAttn: Discovering Cognitive Transition Layers for Efficient Long-Context Prefilling
13. NeurIPS 2026Does Compression Imply Generalization? A Minimum Description Length Perspective
14. NeurIPS 2026Effective Context in Transformers: An Analysis of Fragmentation and Tokenization
15. NeurIPS 2026FFTSparse: Relative-Position Correlation Guided Sparse Attention for Long-Context Language Models
16. NeurIPS 2026Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission
17. NeurIPS 2026FracEncoder: Towards Adaptive Cognitive Trajectories via Fractional-Order Context Encoding
18. NeurIPS 2026Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors
19. NeurIPS 2026Generalization Without Compression Penalty: A Stability Analysis of Error Feedback
20. NeurIPS 2026GeneZip: Region-Aware Compression for Long Context DNA Modeling
21. NeurIPS 2026Geometry Matters in Packed 3D Attention
22. NeurIPS 2026Git Context Controller: Manage the Context of Agents by Agentic Git
23. NeurIPS 2026High-arity Sample Compression
24. NeurIPS 2026In-context learning to predict critical transitions in dynamical systems
25. NeurIPS 2026Inadvertent Context Leakage in Language Models
26. NeurIPS 2026Incremental Learning in Transformers for In-Context Associative Recall
27. NeurIPS 2026Large Language Models Develop Belief State Geometry In-Context
28. NeurIPS 2026Leech Lattice Vector Quantization for Efficient LLM Compression
29. NeurIPS 2026LensVLM: Selective Context Expansion for Compressed Visual Representation of Text
30. NeurIPS 2026Logarithmic Depth Suffices for In-Context Gradient Descent
31. NeurIPS 2026Logistic Bandits with $\tilde{O}(\sqrt{dT})$ Regret without Context Diversity Assumptions
32. NeurIPS 2026Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction
33. NeurIPS 2026MoEZip: Routing-Aware KV Cache Compression for Sparse Mixture-of-Experts LLMs
34. NeurIPS 2026NyoomFloat12: Accelerating LLM Inference via Lossless 12-bit Weight Compression
35. NeurIPS 2026On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models
36. NeurIPS 2026Proportionality in Ranking Compression
37. NeurIPS 2026RankVQ: Low-Rank Parameterized Commutative Vector Quantization for KV Cache Compression
38. NeurIPS 2026Residual-Autoregressive Context for 3D Gaussian Splatting Compression
39. NeurIPS 2026ResKV: Residual-based Channel-wise Unstructured Pruning for KV Cache Compression
40. NeurIPS 2026Short-Context Dominance: How Much Local Context Natural Language Actually Needs?
41. NeurIPS 2026SpectralKV: Redundancy-Aware KV Cache Compression via Spectral Coreset Selection
42. NeurIPS 2026SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LLM Serving
43. NeurIPS 2026STAC-R: Subspace-Tracked Activation Compression with Residuals
44. NeurIPS 2026T-ReX: Learning Tile-Reuse Indexes for Structured Model Compression
45. NeurIPS 2026The Price of Choosing Examples: Context Overfitting in Adaptive In-Context Learning
46. NeurIPS 2026Transformers Can Learn Multiclass Classification In-Context: Isotropy Governs Generalization
47. NeurIPS 2026Visual Text Compression as Measure Transport
48. NeurIPS 2026When Less is More: The LLM Scaling Paradox in Context Compression
49. NeurIPS 2026Why Do Time Series Models Need Long Context Windows?
50. NeurIPS 2026Why Transformers Struggle with Distribution-Independent In-Context Learning

FAQ

How many Context Compression papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

365 in total: 39 in 2023, 81 in 2024, 109 in 2025, 136 in 2026.

How many Context Compression papers are at NeurIPS 2026?

NeurIPS 2026 has 50 Context Compression papers, versus 38 the year before.

How many Context Compression papers are at ICLR 2026?

ICLR 2026 has 28 Context Compression papers, versus 32 the year before.

How many Context Compression papers are at ICML 2026?

ICML 2026 has 39 Context Compression papers, versus 20 the year before.

How many Context Compression papers are at CVPR 2026?

CVPR 2026 has 19 Context Compression papers, versus 19 the year before.

Which conference publishes the most Context Compression papers?

NeurIPS, with 123 papers from 2023 to 2026.