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

365 papers, page 7 of 8

301. NeurIPS 2024Causal Context Adjustment Loss for Learned Image Compression
302. NeurIPS 2024ContextGS : Compact 3D Gaussian Splatting with Anchor Level Context Model
303. NeurIPS 2024DiTFastAttn: Attention Compression for Diffusion Transformer Models
304. NeurIPS 2024DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs
305. NeurIPS 2024Efficient Large Multi-modal Models via Visual Context Compression
306. NeurIPS 2024Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
307. NeurIPS 2024ESPACE: Dimensionality Reduction of Activations for Model Compression
308. NeurIPS 2024Euclidean distance compression via deep random features
309. NeurIPS 2024Exploring Context Window of Large Language Models via Decomposed Positional Vectors
310. NeurIPS 2024In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness
311. NeurIPS 2024KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
312. NeurIPS 2024Learning Partitions from Context
313. NeurIPS 2024MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization
314. NeurIPS 2024Make Your LLM Fully Utilize the Context
315. NeurIPS 2024MeLLoC: Lossless Compression with High-order Mechanism Learning
316. NeurIPS 2024MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
317. NeurIPS 2024One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
318. NeurIPS 2024Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
319. NeurIPS 2024S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning
320. NeurIPS 2024SlimGPT: Layer-wise Structured Pruning for Large Language Models
321. NeurIPS 2024SlimSAM: 0.1% Data Makes Segment Anything Slim
322. NeurIPS 2024StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
323. NeurIPS 2024Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
324. NeurIPS 2024Universal In-Context Approximation By Prompting Fully Recurrent Models
325. NeurIPS 2024Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
326. NeurIPS 2024xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
327. CVPR 2023AutoAD: Movie Description in Context
328. CVPR 2023Class-Incremental Exemplar Compression for Class-Incremental Learning
329. CVPR 2023Context De-Confounded Emotion Recognition
330. CVPR 2023Context-Based Trit-Plane Coding for Progressive Image Compression
331. CVPR 2023Discriminator-Cooperated Feature Map Distillation for GAN Compression
332. CVPR 2023Efficient Hierarchical Entropy Model for Learned Point Cloud Compression
333. CVPR 2023Learned Image Compression With Mixed Transformer-CNN Architectures
334. CVPR 2023Leveraging Temporal Context in Low Representational Power Regimes
335. CVPR 2023Motion Information Propagation for Neural Video Compression
336. CVPR 2023Neural Video Compression With Diverse Contexts
337. CVPR 2023TINC: Tree-Structured Implicit Neural Compression
338. CVPR 2023Ultra-High Resolution Segmentation With Ultra-Rich Context: A Novel Benchmark
339. CVPR 2023Video Compression With Entropy-Constrained Neural Representations
340. ICLR 2023$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
341. ICLR 2023A Unified Framework for Soft Threshold Pruning
342. ICLR 2023Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats
343. ICLR 2023Artificial Neuronal Ensembles with Learned Context Dependent Gating
344. ICLR 2023CrAM: A Compression-Aware Minimizer
345. ICLR 2023DFPC: Data flow driven pruning of coupled channels without data.
346. ICLR 2023Generate rather than Retrieve: Large Language Models are Strong Context Generators
347. ICLR 2023How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?
348. ICLR 2023MIMT: Masked Image Modeling Transformer for Video Compression
349. ICLR 2023Pruning Deep Neural Networks from a Sparsity Perspective
350. ICLR 2023RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch

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.