Efficient Multimodal Inference

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RSJEV: Discriminative Remote Sensing Scene Classification with Multimodal Large Language Models
Oct 6, 2026Dongchen Si, Di Wang, Mingzhen Xu +3Remote Sensing Image Understanding Efficient Multimodal Inference
School of Computer Science, Wuhan University, Wuhan 430072, China · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
VisionWeave: Weaving Elastic Visual Representations as a Native Capability of MLLMs
Oct 6, 2026Yuan Feng, Qize Yang, Ruizhe Chen +9Efficient Multimodal Inference Multimodal Large Language Models
University of Science and Technology of China · Alibaba Token Hub, Alibaba Group · The Chinese University of Hong Kong +1
Decide Before You Look: Learning Which Retrieved Memories Deserve Pixels
Oct 6, 2026Youxing LIMemory-Augmented VLMs Efficient Multimodal Inference
The Chinese University of Hong Kong
Efficient Multimodal Inference through Adaptive Acquisition and Sequential Fusion
Oct 5, 2026Payal Mohapatra, Haodong Yang, Yueyuan Sui +3Efficient Multimodal Inference Multimodal Classification
Arm Inc., USA · Northwestern University, USA
Conditional Trajectory Peaks: Single-Pass Multimodal Policies over Action Chunks
Oct 5, 2026Di Wu, Rongtian Shen, Ping Liu +4Efficient Multimodal Inference Robot Policy Learning
Magiclab Robotics Technology Co., Ltd., China · Southeast University, Nanjing, China
ReMAP: Restoring the Perceptual Cycle with Reasoning-Time Latent Visual Memory
Oct 4, 2026Hao Jiang, Zhanyu Guo, Chenwei Wu +11Memory-Augmented VLMs Efficient Multimodal Inference
University of Electronic Science and Technology of China · University of Michigan, Ann Arbor · Nanyang Technological University +5
Selection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents
Oct 1, 2026Feiyu Gavin Zhu, Xiaoyu Zhu, Jiqi Yang +9Efficient Multimodal Inference Multimodal Reasoning
Apple · Carnegie Mellon University
HAWK: Rethinking Multimodal Drafting for Speculative Decoding
Sep 30, 2026Wenhan Yang, Anirudh Rao, Ashwin ChandraEfficient Multimodal Inference VLM Distillation
University of California, Los Angeles · Samsung Research America
Learning to Reason with Compressed Context: Ground-Truth-Free Adaptation of OmniLLMs via Self-Distillation
Sep 30, 2026Jianghao Wang, Ke Meng, Jian Li +7Efficient Multimodal Inference Multimodal Large Language Models
School of Computer Science, Wuhan University · Didi Chuxing
DecoMoE: Decoupling Visual Propagation and Expert Computation for Efficient Multimodal MoE Inference
Sep 30, 2026Xudong Tan, Peng Ye, Ming Xie +4Mixture-of-Experts Pruning Efficient Multimodal Inference
Fudan University · The Chinese University of Hong Kong
Task-Oriented Visual Feature Compression via Residual Vector Quantization for Device-Edge Multimodal Inference
Sep 29, 2026Luning Pang, Cheng Yuan, Jiawei Shao +2Efficient Multimodal Inference Visual Token Compression
Department of Electronic Engineering, and Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China · Institute of Artificial Intelligence (TeleAI), China Telecom, Beijing 100033, China
OmniRoute: Mapping Temporal Semantic Evidence to Audio-Visual Token Budgets for Efficient Omnimodal Large Language Models
Sep 29, 2026Yuchen Deng, Zidang Cai, Feidiao Yang +4Efficient Multimodal Inference Audio Token Compression
Shenzhen International Graduate School, Tsinghua University, China · Pengcheng Laboratory, China
SPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models
Sep 28, 2026Tianxiang Chen, Zhentao Tan, Zi Ye +9Efficient Multimodal Inference Transformer
End-User Intelligent Computing BU, Alibaba Cloud · Alibaba Group · Department of Computer Science, Maynooth University +2
Just MLPs: Efficient Visual State Reconstruction for Multimodal Language Models
Sep 28, 2026Jingdi lei, Junxian Li, Di Zhang +3Efficient Multimodal Inference Multimodal Large Language Models
Nanyang Technological University · Shanghai Jiao Tong University · Fudan University +2
Resolution as a First-Class Decision: Task-Conditioned Routing for Efficient Multimodal Large Language Models
Sep 28, 2026Zhiqiang Xia, Yang Li, Xinyuan Zhang +5Efficient Multimodal Inference Efficient VLM Inference
Xiaomi Corporation, Beijing, China
OmniTide: Co-Designing Algorithms and Systems for Efficient On-Device Omni-LLM Streaming
Sep 28, 2026Zongshang Shen, Wangsong Yin, Daliang Xu +2Efficient Multimodal Inference On-Device Language Model Inference
Key Lab of High Confidence Software Technologies (Peking University), Beijing, China · State Key Laboratory of Networking and Switching Technology (BUPT), Beijing, China
MiCo: Mutual Information Coverage Optimization through Semantic Erasure Modeling for Efficient MLLM Inference
Sep 28, 2026Tinghao Wang, Yichen Guo, Qizhe Zhang +11Efficient Multimodal Inference Multimodal Large Language Models
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · University of Electronic Science and Technology of China · Nanyang Technological University +2
MAD-Guard: Controlled Study of Autoregressive Generation versus Direct Decision Interfaces for Closed Multimodal Forensic Tasks
Sep 27, 2026Hao ChenEfficient Multimodal Inference Image Forgery Detection
School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou, China
GraphSelect for Budgeted Representation Selection in Multimodal Graph Inference
Sep 27, 2026Xu Wang, Xunkai Li, Yinlin Zhu +1Efficient Multimodal Inference Multimodal Classification
School of Airspace Science and Engineering, Shandong University, Weihai, China · Department of Computer Science, Beijing Institute of Technology, Beijing, China · School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
VaME: Exploring Variational Latent Reasoning for Multimodal Embeddings
Sep 27, 2026Peixi Wu, Mingzhou Jiang, Feipeng Ma +11Multimodal IR Efficient Multimodal Inference
University of Science and Technology of China · Tsinghua University · Kuaishou +1
PARSEE-VAD: Efficient Training-Free Online Video Anomaly Detection via Proposition-Aware Reasoning and Streaming Evidence Escalation
Sep 27, 2026Ji Wang, Shuangqing Zhang, Guo-Sen Xie +1Efficient Multimodal Inference Streaming Video Understanding
Global Institute of Future Technology Shanghai Jiao Tong University Shanghai, 200240, China · School of Intelligence Science and Technology Nanjing University Suzhou, 215163, China · School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing, 210094, China
SLICEChat: Progressive In-Encoder Token Pruning for Whole-Slide Pathology Language Models
Sep 21, 2026Ali Kerem Bozkurt, Baris Cem Bakay, Ibrahim Kulac +3Efficient Multimodal Inference Multimodal Large Language Models
Kocı University, Department of Computer Engineering · Kocı University, Department of Pathology · Hacettepe University, Department of Artificial Intelligence and Data Engineering
Layer-Aware Position Embeddings for Visual Token Pruning in Multimodal Large Language Models
Sep 20, 2026Yahong Wang, Zhangkai Ni, Juncheng Wu +3Efficient Multimodal Inference Multimodal Large Language Models
Tongji University · University of California, Santa Cruz · East China Normal University +1
Efficient Unified Multimodal Understanding (EUMU): Winning Solution for the MUMU Track at the 8th LSVOS Challenge
Sep 16, 2026Dayoung Kil, Seong-heum KimOpen-Vocabulary Object Detection Efficient Multimodal Inference
Department of Intelligent Semiconductors, Soongsil University, Seoul, Republic of Korea
From Models to Systems: A Comprehensive Survey of Efficient Multimodal Learning
Sep 16, 2026Pan Wang, Siwei Song, Hui Ji +12Efficient Multimodal Inference Multimodal Optimization
University of Pittsburgh · New York University · Carnegie Mellon University +6
RankGround: Efficient High-Resolution GUI Grounding via Lightweight Reranker-Guided Crop Selection
Sep 16, 2026Liyang Fan, Xinping Bi, Yitai Li +3Efficient Multimodal Inference Multimodal Reranking
College of Computer Science and Software Engineering Shenzhen University Shenzhen, China · Shenzhen Key Laboratory for High Performance Data Mining Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen, China · Shenzhen University of Advanced Technology Shenzhen, China
Reason What Matters: Retrieval-Grounded Reasoning for Universal Multimodal Embeddings
Sep 14, 2026Mingzhou Jiang, Peixi Wu, Hang Cheng +7Multimodal IR Efficient Multimodal Inference
Tsinghua Shenzhen International Graduate School, Tsinghua University · School of Artificial Intelligence and Data Science, USTC · Kuaishou Technology +1
AdaVSkip: Adaptive Visual Token Skipping Across Layers For Efficient MLLMs Inference
Sep 14, 2026Yuyao Sun, Tao Deng, Shuang Li +1Efficient Multimodal Inference Multimodal Large Language Models
Beihang University
LGFN: Lightweight Gated RGB-Polarization Fusion with Modality-Availability Conditioning for Camouflaged Object Detection
Sep 14, 2026Zhuangfan Huang, Xiaosong Li, Yang Liu +2Missing-Modality Learning Efficient Multimodal Inference
Guangdong-HongKong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, School of Physics and Optoelectronic Engineering, Foshan University, Foshan 528225, China. · School of Mechanical and Electrical Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.
EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression
Sep 11, 2026Motahare Mounesan, Irfan KhanEfficient Multimodal Inference Edge Computing
Texas A&M University

Oct 6, 2026, cs.CVJ/K move · Enter open · S save

RSJEV: Discriminative Remote Sensing Scene Classification with Multimodal Large Language Models

Dongchen Si, Di Wang, Mingzhen Xu, Jing Zhang+2

School of Computer Science, Wuhan University, Wuhan 430072, China · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Remote Sensing Image Understanding Efficient Multimodal Inference Multimodal Large Language Models Multimodal Classification

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Remote sensing scene classification is a fundamental task in Earth observation and geospatial analysis. Existing approaches mainly follow three paradigms: task-specific visual classification, vision-language similarity matching, and autoregressive multimodal generation. However, visual classifiers rely on predefined label spaces, CLIP-based methods perform recognition through static image-text alignment, and multimodal large language models (MLLMs) introduce unnecessary token-level generation for classification tasks with explicit candidate categories. To address these limitations, we propose RSJEV, a one-pass multimodal decision framework for remote sensing scene classification. Unlike conventional MLLMs that formulate classification as autoregressive text generation, RSJEV reformulates scene classification as a candidate-conditioned multimodal discriminative decision process, where visual representations, task instructions, and candidate category semantics are jointly modeled. Specifically, we introduce a OnePass Decider that extracts multimodal decision states and directly estimates category probabilities within the candidate category space, eliminating autoregressive decoding while preserving vision-language interactions. Extensive experiments on three widely used remote sensing scene classification benchmarks, including UC Merced, AID, and NWPU-RESISC45, demonstrate that RSJEV achieves superior classification performance compared with representative CNN-, Transformer-, Mamba-, CLIP-, and MLLM-based methods. Moreover, RSJEV significantly reduces inference costs and achieves a better accuracy-efficiency trade-off with only a compact 0.8B-parameter model. These results demonstrate the effectiveness of state-conditioned multimodal decision making for efficient remote sensing image understanding. The code will be available at https://github.com/Dongtcs/RSJEV.

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