Efficient VLM Inference

VLM: Vision-Language Model

Follow this topic Ask about this topic

Momentum

38 papers in the last four weeks, up 100% on the four weeks before. 0.4% of all new papers.

Jul 13Week of Sep 28

Latest papers 322

All topics

Exploiting answer-invariant redundancies in satellite imagery for efficient VLM inference on edge
Sep 24, 2026Ishani Janveja, Davis Zhang, Seoyul Oh +1Remote Sensing Image Understanding Remote Sensing VQA
University of Illinois Urbana-Champaign
Visual Jev: Accurate and Efficient Decisions from Shared Visual Context
Sep 22, 2026Guanxu Yu, Yuhang YaoVisual Question Answering Efficient Inference
Independent Research · Carnegie Mellon University
SPHQuant: Efficient extreme low bit weight quantization for Vision-Language Models
Sep 21, 2026Kewei Zhang, Zheng Chen, Haotong Qin +1VLM Quantization Efficient VLM Inference
Shanghai Jiao Tong University · The Hong Kong Polytechnic University
VPRune: Efficient Training-free Pre-LLM Visual Token Pruning
Sep 21, 2026Guangchuan Lv, Dianxing Shi, Dingjie FuEfficient VLM Inference Large Vision-Language Models
Northeastern University · Beihang University · Huazhong University of Science and Technology
Region-Level Policy Optimization for Fine-grained MLLM Perception
Sep 17, 2026Yuheng Shi, Xiaohuan Pei, Minjing Dong +1Efficient VLM Inference Large Vision-Language Models
University of Sydney · City University of Hong Kong
MiX: Micro-Inverted-Scaling for End-to-End Low-Bit Vision-Language Model Acceleration
Sep 17, 2026Yuan Liao, Jae-sun SeoAI Accelerator Inference VLM Quantization
Cornell Tech, Cornell University New York, NY, USA
BrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Models
Sep 15, 2026Yihui Peng, Guorui Lu, Qinyu ChenVisual Question Answering Efficient VLM Inference
Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands
StackTok: Accelerating VLMs Inference with Budget-Adaptive Visual Token Selection
Sep 15, 2026Zhenbin Wang, Lei Zhang, Lituan Wang +3Vision-Language Models Efficient VLM Inference
Sichuan University
VideoMM: Adaptive Macro-Micro Inference for Efficient Video MLLMs
Sep 15, 2026Haoyu Guo, Yuan Feng, Junlin Lv +3Efficient VLM Inference Long-Video Understanding
School of Biomedical Engineering, University of Science and Technology of China · Data Darkness Lab, MIRACLE Center, Suzhou Institute for Advanced Research · China +1
Efficient Quantization-Aware Distillation with Cross-Modal Alignment for Edge Vision-Language Models
Sep 15, 2026Jinwoo Jeon, GyuYeop Do, Yubin Lim +4VLM Quantization Efficient VLM Inference
Korea University · Seoul National University
Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding
Sep 11, 2026Weitong Cai, Hang Zhang, Yukai Huang +6Memory-Augmented VLMs Efficient VLM Inference
Queen Mary University of London · Independent Researcher · Durham University +2
Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs
Sep 9, 2026Killian Steunou, Yannis Tevissen, Mounîm A. El YacoubiAudio-Visual Understanding Efficient VLM Inference
SAMOVAR Laboratory, T´el´ecom SudParis, Institut Polytechnique de Paris, Palaiseau, France · Moments Lab, Paris, France
Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs
Sep 9, 2026Haiji Liang, Pengfei Zhou, Zhenglin Wan +3Efficient VLM Inference Large Vision-Language Models
National University of Singapore · InfRec, Cardinal AI Lab · The Hong Kong University of Science and Technology
CoFiE: Coarse-to-Fine Evidence Selection for Efficient Streaming Video Understanding
Sep 3, 2026Jing Jiang, Yiran Ling, Ruonan Li +2Streaming Video Understanding Efficient VLM Inference
Harbin Institute of Technology · State Key Laboratory of Smart Farm Technologies and Systems · Pengcheng Laboratory
Jina-OCR-v1: Efficient Document Parsing with Speculative Decoding and Dense Verifiable Rewards
Sep 2, 2026Alejandro Barón García, Feng Wang, Emilia Garcia Casademont +1Efficient VLM Inference Speculative Decoding
Jina AI by Elastic · New Montgomery Street, San Francisco, CA 94105, USA
Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization
Sep 2, 2026Qingchan Zhu, Weihang You, Hanqi Jiang +3Efficient VLM Inference Visual Token Pruning
School of Computing, University of Georgia · College of Engineering, Northeastern University
S $^2$ Prune: Spatially Structured Visual Token Pruning for Multimodal Large Language Models
Sep 1, 2026Yuanyuan Jia, Shunpu Tang, Qianqian YangEfficient VLM Inference Multimodal Large Language Models
College of Information Science and Electronic Engineering, Zhejiang University Hangzhou, China
SinkPruner: Sink-Free Visual Token Pruning for Multimodal Large Language Models
Sep 1, 2026Shiyu Li, Zi-Yuan Hu, Shijia Huang +3Efficient VLM Inference Multimodal Large Language Models
1The Chinese University of Hong Kong · 2Weitu AI · 3Peking University
VerNav: Verifier-First Low-Latency Vision-and-Language Navigation
Sep 1, 2026Zhixin Wang, Chengzheyi Yao, Leyuan Liu +2Efficient VLM Inference Vision-Language Navigation
University of Electronic Science and Technology of China
From Saliency to Discriminability: Rank-Preserving Visual Token Pruning for VLM Rerankers
Sep 1, 2026Siyi Liu, Hanjun Yang, Chenchen Zhang +7Efficient VLM Inference Multimodal Reranking
1The Hong Kong University of Science and Technology (Guangzhou) · 2Tencent Yuanbao · 3ARC Lab, Tencent
A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss
Sep 1, 2026Suryaansh Jain, Rahasya Barkur, Vishal G +8Contrastive Learning Image Captioning
University of Massachusetts Amherst · Adobe Research
Vision Is Not Overhead: One-Pass Block Drafting for Lossless Speculative Decoding in Vision-Language Models
Aug 31, 2026Jungseob Lee, Seongtae Hong, Dongyub Jude Lee +4Efficient VLM Inference Speculative Decoding
Korea University · Zoom Communications · Soongsil University +2
StreamScout: Learning When to Look Deeper for Streaming Video Understanding
Aug 31, 2026Ce Zhang, Jing Bi, Jinxi He +9Adaptive Inference Streaming Video Understanding
Carnegie Mellon University · TikTok · University of Rochester +2
Centering before Pruning: Lightweight Geometry Correction for Diversity-Based Visual Token Pruning in LVLMs
Aug 31, 2026Shunjie Wen, Jaeyeon Lee, Dong-Wan ChoiEfficient VLM Inference Large Vision-Language Models
Inha University
PACE: A Unified Condense-and-Extract Paradigm for Fast VLM Inference
Aug 27, 2026Junjie Liu, Shengyuan Ye, Xu ChenEfficient VLM Inference Visual Token Pruning
Sun Yat-sen University · Power Dispatch Control Center, Guangdong Power Grid Co., Ltd. Guangzhou, China · Shenzhen Loop Area Institute, Shenzhen, China
Multi-Image Visual Token Pruning in Large Visual Language Models
Aug 27, 2026Rongyang Zhang, Chengqiang Lu, Cong Li +9Efficient VLM Inference Large Vision-Language Models
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China · Xiaohongshu Inc.
QV-PIC: Query-Aware Visual Position-Independent Caching for Efficient RAG Serving
Aug 12, 2026Yilin Liu, Rui Meng, Wangze Ni +5Retrieval-Augmented Generation KV Caching
Zhejiang University · Department of Statistics and Data Science, Beijing Normal-Hong Kong Baptist University · Microsoft +2
StreamFlow: Dynamic Memory Flows for Streaming Video Understanding
Aug 11, 2026Muxin Fu, Yifan Zhang, Wentao Zhang +5Memory-Augmented VLMs Streaming Video Understanding
Tongji University · Nanyang Technological University · University of Michigan +2
Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language Models
Aug 11, 2026Yuhang Song, Bor-Jiun Lin, Jiaxu Liu +3Memory-Augmented VLMs Vision-Language Models
Department of Computer Science, University of Liverpool · Department of Computer Science, National Tsinghua University · Imperial College London +1
When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs
Aug 11, 2026Congyang Ou, Ruike Song, Yang Zhou +3Efficient VLM Inference Large Vision-Language Models
Northwestern Polytechnical University · Chongqing University · MiLM Plus, Xiaomi Inc.

Sep 24, 2026, cs.CVJ/K move · Enter open · S save

Exploiting answer-invariant redundancies in satellite imagery for efficient VLM inference on edge

Ishani Janveja, Davis Zhang, Seoyul Oh, Deepak Vasisht

University of Illinois Urbana-Champaign

Remote Sensing Image Understanding Remote Sensing VQA Efficient VLM Inference Remote Sensing Visual Token Pruning

Open paper AskPDF arXiv

Onboard vision-language models could enable satellites to answer queries directly, but exhaustive tiled inference over high-resolution imagery is slow and energy-intensive. We identify answer-invariant token redundancy (AITR): image tiles and vision tokens that can be removed without changing the final answer. We present Rift, a two-stage system that performs query-conditioned tile pruning followed by elastic prefill to reduce token budget. We evaluate it on LLaVA-1.5 7B running on Jetson AGX Orin. Compared with exhaustive tiled inference, Rift reduces energy by 78% and latency by 69%, while increasing accuracy from 45% to 73%.

Momentum

Related topics

Latest papers 322