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

298 papers, page 3 of 6

101. NeurIPS 2026SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking
102. NeurIPS 2026Short-Context Dominance: How Much Local Context Natural Language Actually Needs?
103. NeurIPS 2026SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks
104. NeurIPS 2026SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining
105. NeurIPS 2026SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference
106. NeurIPS 2026SpectralKV: Redundancy-Aware KV Cache Compression via Spectral Coreset Selection
107. NeurIPS 2026SurgVista: Long-Horizon Surgical World Modeling with Plausible Instrument-Tissue Dynamics
108. NeurIPS 2026SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference
109. NeurIPS 2026SWE-Marathon: Can AI Agents Autonomously Complete Ultra-Long-Horizon Software Work?
110. NeurIPS 2026Test time training enhances in-context learning of nonlinear functions
111. NeurIPS 2026The $1/\mathcal{W}$ Law: Context Length is the Dominant Energy Lever in LLM Inference Fleets
112. NeurIPS 2026The Key to Going Linear: Analysis-Driven Transformer Linearization
113. NeurIPS 2026The Long-Run Distribution of Regularized Learning in Non-Concave Games: A Large Deviations Approach
114. NeurIPS 2026The PokeAgent Challenge: Competitive and Long-Context Learning at Scale
115. NeurIPS 2026The Price of Choosing Examples: Context Overfitting in Adaptive In-Context Learning
116. NeurIPS 2026To Copy or Not to Copy: Controlling Speculative Decoding via Intrinsic Model Signals
117. NeurIPS 2026Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context
118. NeurIPS 2026Transformers Can Learn Multiclass Classification In-Context: Isotropy Governs Generalization
119. NeurIPS 2026Trimming the Long-Tail of Visual World Modeling Evaluation
120. NeurIPS 2026TSFM Meets LLM: Context as Covariate
121. NeurIPS 2026TStruct: Learning Shared Temporal Structures for Long-Term Time-Series Forecasting
122. NeurIPS 2026UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification
123. NeurIPS 2026UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence
124. NeurIPS 2026VINCIE-NExT: Unlocking Video Editing from Images via In-Context Modeling
125. NeurIPS 2026Virtual Head Attention
126. NeurIPS 2026VL-DocIR: A Benchmark for Vision-Based Long Document Retrieval
127. NeurIPS 2026Volatility-Whitened Probabilistic Residual Modeling for Long-Term Time Series Forecasting
128. NeurIPS 2026What Remains in Sight? Autoregressive Video Decoding as Representation-Guided Context Rewriting
129. NeurIPS 2026Why Do Time Series Models Need Long Context Windows?
130. NeurIPS 2026Why Transformers Struggle with Distribution-Independent In-Context Learning
131. NeurIPS 2025A Controllable Examination for Long-Context Language Models
132. NeurIPS 2025A Little Depth Goes a Long Way: The Expressive Power of Log-Depth Transformers
133. NeurIPS 2025Absence Bench: Language Models Can’t See What’s Missing
134. NeurIPS 2025AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
135. NeurIPS 2025AttentionPredictor: Temporal Patterns Matter for KV Cache Compression
136. NeurIPS 2025Block-Biased Mamba for Long-Range Sequence Processing
137. NeurIPS 2025ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
138. NeurIPS 2025Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers
139. NeurIPS 2025Constant Bit-size Transformers Are Turing Complete
140. NeurIPS 2025Context-Aware Regularization with Markovian Integration for Attention-Based Nucleotide Analysis
141. NeurIPS 2025ConTextTab: A Semantics-Aware Tabular In-Context Learner
142. NeurIPS 2025CORAL: Disentangling Latent Representations in Long-Tailed Diffusion
143. NeurIPS 2025DeepHalo: A Neural Choice Model with Controllable Context Effects
144. NeurIPS 2025Disentangling Latent Shifts of In-Context Learning with Weak Supervision
145. NeurIPS 2025DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
146. NeurIPS 2025Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language Models
147. NeurIPS 2025Effects of Dropout on Performance in Long-range Graph Learning Tasks
148. NeurIPS 2025Efficient Low Rank Attention for Long-Context Inference in Large Language Models
149. NeurIPS 2025Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference
150. NeurIPS 2025Enhancing the Maximum Effective Window for Long-Term Time Series Forecasting

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.