Long Context papers, 2023–2026

Key findings

• Long Context went from 66 papers in 2023 to 341 in 2026, roughly 5.2x in three years.
• NeurIPS publishes the most Long Context work: 298 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with AI Agents: papers tagged with both rose from 0 in 2023 to 45 in 2026.
• Among the 5 topics under Long Context and Memory, it ranks #1 by 2026 paper count; the fastest grower in the group, Retrieval Memory, is up 6.6x versus 5.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Accelerating Long-Context LLM Prefill via Layer-wise Progressive Token Pruning in Local Deployment
• ICML 2026AdaSplash-2: Faster Differentiable Sparse Attention
• ICLR 2026An evolutionary perspective on modes of learning in Transformers
• CVPR 2026AR2-4FV Anchored Referring and Re-identification for Long-Term Grounding in Fixed-View
• NeurIPS 2025A Controllable Examination for Long-Context Language Models
• ICML 2025CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
• ICLR 2025$\text{D}_{2}\text{O}$: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models
• CVPR 2025BIMBA: Selective-Scan Compression for Long-Range Video Question Answering
• NeurIPS 2024[Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition
• ICML 2024Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
• ICLR 2024CLEX: Continuous Length Extrapolation for Large Language Models
• CVPR 2024GigaTraj: Predicting Long-term Trajectories of Hundreds of Pedestrians in Gigapixel Complex Scenes
• NeurIPS 2023A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation
• ICML 2023CAB: Comprehensive Attention Benchmarking on Long Sequence Modeling
• ICLR 2023$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
• CVPR 2023AutoAD: Movie Description in Context
• NeurIPS 2026AdaCal: Adaptive Calibration for Robust Sparse Attention in Long-Context LLMs
• ICML 2026Artificial Hippocampus Networks for Efficient Long-Context Modeling
• ICLR 2026AutoSP: Unlocking Long-Context LLM Training Via Compiler-Based Sequence Parallelism
• CVPR 2026AstraNav-Memory Contexts Compression for Long Memory

All Long Context papers

255 papers, page 4 of 6

151. ICML 2025Test-Time Training Provably Improves Transformers as In-context Learners
152. ICML 2025TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
153. ICML 2025Training Dynamics of In-Context Learning in Linear Attention
154. ICML 2025TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories
155. ICML 2025Understanding and Improving Length Generalization in Recurrent Models
156. ICML 2025Understanding Synthetic Context Extension via Retrieval Heads
157. ICML 2025VideoRoPE: What Makes for Good Video Rotary Position Embedding?
158. NeurIPS 2025A Controllable Examination for Long-Context Language Models
159. NeurIPS 2025A Little Depth Goes a Long Way: The Expressive Power of Log-Depth Transformers
160. NeurIPS 2025Absence Bench: Language Models Can’t See What’s Missing
161. NeurIPS 2025AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
162. NeurIPS 2025AttentionPredictor: Temporal Patterns Matter for KV Cache Compression
163. NeurIPS 2025Block-Biased Mamba for Long-Range Sequence Processing
164. NeurIPS 2025ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
165. NeurIPS 2025Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers
166. NeurIPS 2025Constant Bit-size Transformers Are Turing Complete
167. NeurIPS 2025Context-Aware Regularization with Markovian Integration for Attention-Based Nucleotide Analysis
168. NeurIPS 2025ConTextTab: A Semantics-Aware Tabular In-Context Learner
169. NeurIPS 2025CORAL: Disentangling Latent Representations in Long-Tailed Diffusion
170. NeurIPS 2025DeepHalo: A Neural Choice Model with Controllable Context Effects
171. NeurIPS 2025Disentangling Latent Shifts of In-Context Learning with Weak Supervision
172. NeurIPS 2025DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
173. NeurIPS 2025Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language Models
174. NeurIPS 2025Effects of Dropout on Performance in Long-range Graph Learning Tasks
175. NeurIPS 2025Efficient Low Rank Attention for Long-Context Inference in Large Language Models
176. NeurIPS 2025Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference
177. NeurIPS 2025Enhancing the Maximum Effective Window for Long-Term Time Series Forecasting
178. NeurIPS 2025FLAME: Fast Long-context Adaptive Memory for Event-based Vision
179. NeurIPS 2025FlashMD: long-stride, universal prediction of molecular dynamics
180. NeurIPS 2025FlexSelect: Flexible Token Selection for Efficient Long Video Understanding
181. NeurIPS 2025From Softmax to Score: Transformers Can Effectively Implement In-Context Denoising Steps
182. NeurIPS 2025Hardware-aligned Hierarchical Sparse Attention for Efficient Long-term Memory Access
183. NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
184. NeurIPS 2025Hierarchical Demonstration Order Optimization for Many-shot In-Context Learning
185. NeurIPS 2025Hierarchical Implicit Neural Emulators
186. NeurIPS 2025HiFC: High-efficiency Flash-based KV Cache Swapping for Scaling LLM Inference
187. NeurIPS 2025Homogeneous Keys, Heterogeneous Values: Exploiting Local KV Cache Asymmetry for Long-Context LLMs
188. NeurIPS 2025HoPE: Hybrid of Position Embedding for Long Context Vision-Language Models
189. NeurIPS 2025How Data Mixing Shapes In-Context Learning: Asymptotic Equivalence for Transformers with MLPs
190. NeurIPS 2025In-Context Compositional Learning vis Sparse Coding Transformer
191. NeurIPS 2025In-Context Learning Strategies Emerge Rationally
192. NeurIPS 2025KeyDiff: Key Similarity-Based KV Cache Eviction for Long-Context LLM Inference in Resource-Constrained Environments
193. NeurIPS 2025Know Thyself by Knowing Others: Learning Neuron Identity from Population Context
194. NeurIPS 2025KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction
195. NeurIPS 2025L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models
196. NeurIPS 2025L$^2$M: Mutual Information Scaling Law for Long-Context Language Modeling
197. NeurIPS 2025Language Models (Mostly) Know When to Stop Reading
198. NeurIPS 2025Learning to Focus: Causal Attention Distillation via Gradient‐Guided Token Pruning
199. NeurIPS 2025Let Me Think! A Long Chain of Thought Can Be Worth Exponentially Many Short Ones
200. NeurIPS 2025Linear Transformers Implicitly Discover Unified Numerical Algorithms

FAQ

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

838 in total: 66 in 2023, 176 in 2024, 255 in 2025, 341 in 2026.

How many Long Context papers are at NeurIPS 2026?

NeurIPS 2026 has 130 Long Context papers, versus 98 the year before.

How many Long Context papers are at ICLR 2026?

ICLR 2026 has 82 Long Context papers, versus 87 the year before.

How many Long Context papers are at ICML 2026?

ICML 2026 has 98 Long Context papers, versus 53 the year before.

How many Long Context papers are at CVPR 2026?

CVPR 2026 has 31 Long Context papers, versus 17 the year before.

Which conference publishes the most Long Context papers?

NeurIPS, with 298 papers from 2023 to 2026.