Long-Context VLMs

VLM: Vision-Language Model

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Overview

Long-context VLMs study how models can find and reason over relevant visual evidence in long documents, videos, and ongoing multimodal conversations. Approaches include extending context during training, retrieving relevant pages or frames, compressing visual tokens, and adding structured or recurrent memory and tool-using agents. Evaluation spans document question answering benchmarks such as MMLongBench-Doc and long-video benchmarks such as VideoMME and LongVideoBench, with growing attention to evidence grounding and multi-session memory. The central tension is how to reduce context and memory costs without discarding fine-grained details or the connections needed for reliable reasoning.

Latest papers

CardsList

46 papers9 papers in the last four weeks, up 13% on the four weeks before. 0.1% of all new papers.

  1. POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs

    Apr 13, 2026Haicheng Wang, Yuan Liu, Yikun Liu +9Multimodal Large Language ModelsLong-Context VLMs

    SAI, Shanghai Jiao Tong University, China · WeChat AI, Tencent, China

  2. EXAONE 4.5 Technical Report

    Apr 9, 2026Eunbi Choi, Kibong Choi, Sehyun Chun +55Vision-Language ModelsLarge Vision-Language Models

  3. DetailVerifyBench: A Benchmark for Dense Hallucination Localization in Long Image Captions

    Apr 7, 2026Xinran Wang, Yuxuan Zhang, Xiao Zhang +7VLM HallucinationVLM Evaluation

    Beijing University of Posts and Telecommunications, Beijing, China

  4. Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects

    Apr 7, 2026Jun Zhang, Yicheng Ji, Feiyang Ren +7Efficient VLM InferenceLarge Vision-Language Models

    The State Key Laboratory of Blockchain and Data Security, Zhejiang University · Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security

  5. Internalized Reasoning for Long-Context Visual Document Understanding

    Mar 31, 2026Austin VeselkaMultimodal UnderstandingDocument Image Understanding

    LightOn

  6. V-CAST: Video Curvature-Aware Spatio-Temporal Pruning for Efficient Video Large Language Models

    Mar 29, 2026Xinying Lin, Xuyang Liu, Yiyu Wang +2Efficient VLM InferenceVideo Token Compression

    Shenzhen Campus of Sun Yat-sen University · Shenzhen Loop Area Institute · Sichuan University +1

  7. Falcon Perception

    Mar 28, 2026Aviraj Bevli, Sofian Chaybouti, Yasser Dahou +6Large Vision-Language ModelsLong-Context VLMs

    Falcon Vision Team, TII

  8. LensWalk: Agentic Video Understanding by Planning How You See in Videos

    Mar 25, 2026Keliang Li, Yansong Li, Hongze Shen +3Video ReasoningTemporal Video Understanding

    Institute of Computing Technology, Chinese Academy of Sciences, China · University of Chinese Academy of Sciences, China · College of Computer Science and Electronic Engineering, Hunan University, China +1

  9. Attention-aware Inference Optimizations for Large Vision-Language Models with Memory-efficient Decoding

    Mar 25, 2026Fatih Ilhan, Gaowen Liu, Ramana Rao Kompella +5Efficient VLM InferenceLarge Vision-Language Models

    Georgia Institute of Technology · Cisco Research

  10. Event-Anchored Frame Selection for Effective Long-Video Understanding

    Mar 1, 2026Wang Chen, Yongdong Luo, Yuhui Zeng +5Video Frame SelectionQuery-Aware Video Frame Selection

    Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University · College of Computer and Data Science, Fuzhou University

  11. CLIP Is Shortsighted: Paying Attention Beyond the First Sentence

    Feb 25, 2026Marc-Antoine Lavoie, Anas Mahmoud, Aldo Zaimi +2Position Bias in VLMsVision-Language Alignment

    University of Toronto Robotics Institute · Mila - Quebec AI Institute

  12. Visual Memory Injection Attacks for Multi-Turn Conversations

    Feb 17, 2026Christian Schlarmann, Matthias HeinBackdoor Attacks on VLA ModelsBackdoor Attacks on VLMs

    Tübingen AI Center, University of Tübingen, Germany

  13. Sparrow: Text-Anchored Window Attention with Visual-Semantic Glimpsing for Speculative Decoding in Video LLMs

    Feb 17, 2026Libo Zhang, Zhaoning Zhang, Wangyang Hong +2Speculative DecodingLong-Context VLMs

    National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology, Changsha, China.

  14. How to Train Your Long-Context Visual Document Model

    Feb 16, 2026Austin VeselkaVisual Question AnsweringVision-Language Models

    LightOn

  15. Seeing to Generalize: How Visual Data Corrects Binding Shortcuts

    Feb 16, 2026Nicolas Buzeta, Felipe del Rio, Cristian Hinostroza +3Cross-Modal LearningShortcut Learning

    Department of Computer Science, Pontificia Universidad Católica, Santiago, Chile · 2Centro Nacional de Inteligencia Artificial (CENIA), Santiago, Chile · 3Instituto Milenio en Ingeniería e Inteligencia Artificial para la Salud (iHEALTH), Santiago, Chile.

  16. How Well Do Vision-Language Models Understand Movies?

    Jun 6, 2025Emmanouil Zaranis, António Farinhas, Saul Santos +28Video-Language Model EvaluationMultimodal Understanding

    Instituto Superior Técnico, Universidade de Lisboa · Instituto de Telecomunicações · ILLC, University of Amsterdam +12