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 5 of 8

201. ICML 2025ParallelComp: Parallel Long-Context Compressor for Length Extrapolation
202. ICML 2025Prompt-based Depth Pruning of Large Language Models
203. ICML 2025Retraining-free Merging of Sparse MoE via Hierarchical Clustering
204. ICML 2025RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
205. ICML 2025SkipGPT: Each Token is One of a Kind
206. ICML 2025Training Dynamics of In-Context Learning in Linear Attention
207. ICML 2025Weight matrices compression based on PDB model in deep neural networks
208. NeurIPS 2025AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
209. NeurIPS 2025AttentionPredictor: Temporal Patterns Matter for KV Cache Compression
210. NeurIPS 2025Binary Quadratic Quantization: Beyond First-Order Quantization for Real-Valued Matrix Compression
211. NeurIPS 2025Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression
212. NeurIPS 2025ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
213. NeurIPS 2025COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation
214. NeurIPS 2025Conditional Distribution Compression via the Kernel Conditional Mean Embedding
215. NeurIPS 2025Constant Bit-size Transformers Are Turing Complete
216. NeurIPS 2025DeepHalo: A Neural Choice Model with Controllable Context Effects
217. NeurIPS 2025Disentangling Latent Shifts of In-Context Learning with Weak Supervision
218. NeurIPS 2025Don't Just Chase “Highlighted Tokens” in MLLMs: Revisiting Visual Holistic Context Retention
219. NeurIPS 2025DUO: No Compromise to Accuracy Degradation
220. NeurIPS 2025Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference
221. NeurIPS 2025End-to-End Low-Light Enhancement for Object Detection with Learned Metadata from RAWs
222. NeurIPS 2025FP4 All the Way: Fully Quantized Training of Large Language Models
223. NeurIPS 2025From Softmax to Score: Transformers Can Effectively Implement In-Context Denoising Steps
224. NeurIPS 2025Homogeneous Keys, Heterogeneous Values: Exploiting Local KV Cache Asymmetry for Long-Context LLMs
225. NeurIPS 2025In-Context Compositional Learning vis Sparse Coding Transformer
226. NeurIPS 2025InfiniPot-V: Memory-Constrained KV Cache Compression for Streaming Video Understanding
227. NeurIPS 2025KeyDiff: Key Similarity-Based KV Cache Eviction for Long-Context LLM Inference in Resource-Constrained Environments
228. NeurIPS 2025KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction
229. NeurIPS 2025Language Models (Mostly) Know When to Stop Reading
230. NeurIPS 2025Large Language Models for Lossless Image Compression: Next-Pixel Prediction in Language Space is All You Need
231. NeurIPS 2025LittleBit: Ultra Low-Bit Quantization via Latent Factorization
232. NeurIPS 2025MoRIC: A Modular Region-based Implicit Codec for Image Compression
233. NeurIPS 2025Neural Attention Search
234. NeurIPS 2025Neural B-frame Video Compression with Bi-directional Reference Harmonization
235. NeurIPS 2025Overcoming Long Context Limitations of State Space Models via Context Dependent Sparse Attention
236. NeurIPS 2025Scale-invariant attention
237. NeurIPS 2025SmallKV: Small Model Assisted Compensation of KV Cache Compression for Efficient LLM Inference
238. NeurIPS 2025Stochastic Forward-Forward Learning through Representational Dimensionality Compression
239. NeurIPS 2025Theoretical Insights into In-context Learning with Unlabeled Data
240. NeurIPS 2025UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression
241. NeurIPS 2025Unlabeled Data Can Provably Enhance In-Context Learning of Transformers
242. NeurIPS 2025Value-Guided KV Compression for LLMs via Approximated CUR Decomposition
243. NeurIPS 2025Vision-centric Token Compression in Large Language Model
244. NeurIPS 2025Vocabulary In-Context Learning in Transformers: Benefits of Positional Encoding
245. NeurIPS 2025zip2zip: Inference-Time Adaptive Tokenization via Online Compression
246. CVPR 2024Amodal Completion via Progressive Mixed Context Diffusion
247. CVPR 2024CLiC: Concept Learning in Context
248. CVPR 2024ContextSeg: Sketch Semantic Segmentation by Querying the Context with Attention
249. CVPR 2024Diversity-aware Channel Pruning for StyleGAN Compression
250. CVPR 2024In-Context Matting

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.