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

838 papers, page 15 of 17

701. ICML 2024Memory Consolidation Enables Long-Context Video Understanding
702. ICML 2024Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
703. ICML 2024PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
704. ICML 2024PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels
705. ICML 2024Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
706. ICML 2024Position: Do pretrained Transformers Learn In-Context by Gradient Descent?
707. ICML 2024Position: Key Claims in LLM Research Have a Long Tail of Footnotes
708. ICML 2024QUEST: Query-Aware Sparsity for Efficient Long-Context LLM Inference
709. ICML 2024Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
710. ICML 2024Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences
711. ICML 2024SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
712. ICML 2024SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
713. ICML 2024SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters
714. ICML 2024Training-Free Long-Context Scaling of Large Language Models
715. ICML 2024Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
716. ICML 2024Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape
717. ICML 2024Viewing Transformers Through the Lens of Long Convolutions Layers
718. ICML 2024What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
719. ICML 2024Why Larger Language Models Do In-context Learning Differently?
720. ICML 2024xT: Nested Tokenization for Larger Context in Large Images
721. NeurIPS 2024[Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition
722. NeurIPS 2024An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding
723. NeurIPS 2024AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation
724. NeurIPS 2024BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
725. NeurIPS 2024Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
726. NeurIPS 2024Base of RoPE Bounds Context Length
727. NeurIPS 2024BERTs are Generative In-Context Learners
728. NeurIPS 2024DAPE: Data-Adaptive Positional Encoding for Length Extrapolation
729. NeurIPS 2024Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum
730. NeurIPS 2024Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling
731. NeurIPS 2024Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
732. NeurIPS 2024Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate
733. NeurIPS 2024Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
734. NeurIPS 2024Exploring Context Window of Large Language Models via Decomposed Positional Vectors
735. NeurIPS 2024Flexible Context-Driven Sensory Processing in Dynamical Vision Models
736. NeurIPS 2024Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding
737. NeurIPS 2024Grammar-Aligned Decoding
738. NeurIPS 2024In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness
739. NeurIPS 2024InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory
740. NeurIPS 2024KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
741. NeurIPS 2024Learning Partitions from Context
742. NeurIPS 2024Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models
743. NeurIPS 2024Linear Transformers are Versatile In-Context Learners
744. NeurIPS 2024Long-range Brain Graph Transformer
745. NeurIPS 2024Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
746. NeurIPS 2024Long-tailed Object Detection Pretraining: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
747. NeurIPS 2024LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding
748. NeurIPS 2024Make Your LLM Fully Utilize the Context
749. NeurIPS 2024MambaLRP: Explaining Selective State Space Sequence Models
750. NeurIPS 2024Many-Shot In-Context Learning

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.