Vision-Language Models

Also known as VLM

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55 papers in the last four weeks, up 120% on the four weeks before. 0.5% of all new papers.

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FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval
Jul 2, 2026Zhenqi He, Ziqi Jiang, Yuanpei Liu +3Vision-Language Models Composed Image Retrieval
The Hong Kong University of Science and Technology, Hong Kong SAR · The University of Hong Kong, Hong Kong SAR
MolSight: A Graph-Aware Vision-Language Model for Unified Chemical Image Understanding
Jul 2, 2026Wenda Wang, Yihan Tong, Yuwei Hu +1Vision-Language Models Vision-Language Alignment
Renmin University of China · Beijing
SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models
Jul 2, 2026Qi Lyu, Jiahua Dong, Baichen Liu +7Model Compression Vision-Language Models
State Key Laboratory of Robotics and Intelligent Systems · Shenyang Institute of Automation, Chinese Academy of Sciences · University of Chinese Academy of Sciences +2
LASER: A Corrective Lens for LVLMs via Visual Attention Preservation and Sink Suppression
Jul 2, 2026Bowen Yuan, Zijian Wang, Yadan Luo +2Vision-Language Models Large Vision-Language Models
The University of Queensland
Disentangling Pictorial Cue Understanding from Language Bias in VLMs via Depth Ordering Task
Jul 1, 2026Yiqian Liu, Iuliia Kotseruba, John K. TsotsosVLM Evaluation Vision-Language Models
York University, Toronto, Canada · University of Guelph, Guelph, Canada
Latent Visual Cache for Video Reasoning
Jul 1, 2026Yongheng Zhang, Zhipeng Xu, Hao Wu +4Memory-Augmented VLMs Vision-Language Models
1Tencent Youtu Lab · 2Tsinghua University · University of Illinois at Chicago
AdaBoosting Text Prompts for Vision-Language Models
Jul 1, 2026Seokhee Jin, Changhwan Sung, Sunung Mun +2Vision-Language Models Ensemble Learning
KT Corporation, Republic of Korea · Pohang University of Science and Technology (POSTECH), Republic of Korea · National AI Research Lab, Republic of Korea
Caption Bottleneck Models
Jul 1, 2026Seref Baris Cagliyan, Umut Ozdemir, Merve Tapli +1Vision-Language Models Concept Bottleneck Models
Dept. of Computer Eng., Middle East Technical University (METU) · Robotics & AI Center (ROMER), METU
HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding
Jul 1, 2026Ji Ha Jang, Hayeon Kim, Chulwon Lee +2VLM Robustness Vision-Language Models
1Dept. of Electrical and Computer Engineering, 2IPAI, 3INMC & AIIS, Seoul National University, Republic of Korea
From Accuracy to Visual Dependence: Auditing and Filtering Modality Collapse in Traffic VideoQA
Jun 29, 2026Sena Korkut, María Alejandra Bravo Sarmiento, Sanghwan Kim +1VLM Evaluation Vision-Language Models
Technical University of Munich, Munich, Germany · Helmholtz Zentrum München, Munich, Germany · Munich Center for Machine Learning, Munich, Germany
SHOVIR: A Benchmark for Evaluating Vision Shortcut Learning in Radiology Report Generation
Jun 29, 2026Filippo Ruffini, Marco Salmé, Rosa Sicilia +2VLM Evaluation Radiology Report Generation
Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Universit`a Campus Bio-Medico di Roma, Rome, Italy · Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Ume˚a University, Ume˚a, Sweden · UniCamillus-Saint Camillus International University of Health Sciences, Rome, Italy
RiverONE: Generating Knowledge-Intensive VLM by Simulated Quantum Machines
Jun 29, 2026Xindian Ma, Xinyu Long, Yefei Zhang +11Vision-Language Models Quantum-Inspired ML
Thewake RiverYtz Lab
FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models
Jun 28, 2026Yichen Guo, Kai Tang, Fenglai Lin +5Vision-Language Models Large Vision-Language Models
1Nanyang Technological University · 2State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · 3Tsinghua University
Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking
Jun 28, 2026Xiao Wang, Liye Jin, Dan Xu +5Vision-Language Models Visual Object Tracking
School of Computer Science and Technology, Anhui University, Hefei 230601, China · School of Electronic and Information Engineering, Anhui University, Hefei 230601, China · Harbin Institute of Technology, Shenzhen, China +3
ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models
Jun 27, 2026Guanglong Sun, Shuang Cui, Bo Lei +6Memory-Augmented VLMs Vision-Language Models
School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China · Institute of Software Chinese Academy of Sciences, Beijing, China · 3Beijing Academy of Artificial Intelligence, Beijing, China +2
MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving
Jun 26, 2026Nan Yang, Zhanwen Liu, Linfeng Zhang +4Vision-Language Models VLMs for Autonomous Driving
School of Information Engineering, Chang’an University, China · School of Artificial Intelligence, Shanghai Jiaotong University, China
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models
Jun 24, 2026Haoxiang Sun, Tao Wang, Li Yuan +2Vision-Language Models Multimodal Large Language Models
School of Computer Science, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu, 610065, Sichuan, China · School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, 2199 Lishui Road, Shenzhen, 518055, Guangdong, China · Institute of Artificial Intelligence (TeleAI), China Telecom and Northwestern Polytechnical University, 127 Youyi West Road, Xi’an, 710072, Shaanxi, China
Do vision-language models search like humans? Reasoning tokens as a reaction-time analog in classic visual-search paradigms
Jun 23, 2026Farahnaz WickVLM Evaluation Vision-Language Models
1Independent Researcher
Data Selection Through Iterative Self-Filtering for Vision-Language Settings
Jun 22, 2026Andrei Liviu Nicolicioiu, Sarvjeet Singh Ghotra, Morgane M. Moss +1Vision-Language Models Training Data Curation
Mila, Université de Montréal
FlowTrain: Flow-Based Decoupled Training for Industrial-Grade Vision-Language Models
Jun 22, 2026Zhida Jiang, Zhaolong Xing, Yang Pei +14Vision-Language Models
Huawei
Each Judge Its Own Yardstick: Discovering Per-VLM Taxonomies for Physical Video Evaluation
Jun 22, 2026Yu Cao, Ziquan Liu, Zhensong Zhang +3VLM Evaluation Physical Consistency in Video Generation
Queen Mary University of London · Huawei Darwin Research Center · Imperial College London
OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs
Jun 21, 2026Hao Vo, Phu Loc Nguyen, Khoa Vo +7Multi-View Geometry Vision-Language Models
University of Arkansas, USA · Google Research, Google · University of Liverpool, UK +1
Gold Points Sniper: Self-guided Visual Reasoning in VLM for Fine-grained Action Understanding
Jun 21, 2026Haodi Liu, Xinhang Yang, Kunda Yan +3Vision-Language Models Human Activity Recognition
Beijing National Research Center for Information Science and Technology (BNRist), Department of Automation, Tsinghua University, Beijing, P.R.China · State Key Laboratory of General Artificial Intelligence, Beijing Institute for General Artificial Intelligence (BIGAI).
When Does a Video-Language Model Stop Watching? Reward Strength Controls the Formation and Reversal of Visual Shortcuts in Multimodal RLVR
Jun 20, 2026Zekun XuVision-Language Models Video-Language Models
School of Computer Science, The University of Sydney, Sydney, Australia
The Unreasonable Effectiveness of VLMs for Zero-shot Procedural Mistake Detection
Jun 19, 2026Serdar Ozsoy, Lars Doorenbos, Federico Spurio +2Temporal Action Segmentation Vision-Language Models
University of Bonn · Lamarr Institute for Machine Learning and Artificial Intelligence · Toyota Motor Europe
BIT-Nav: Brain-Inspired Trajectory Memory for Embodied Navigation
Jun 19, 2026Rithvik Jonna, Aakash Gurram, Man Namgung +2Vision-Language Models Embodied Navigation
Department of Electrical and Computer Engineering Johns Hopkins University · Laboratory for Computational Sensing and Robotics Johns Hopkins University · DEVCOM Army Research Laboratory
FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages
Jun 19, 2026Juntong Peng, Qi Chen, Deyuan Qu +3Vision-Language Models VLMs for Autonomous Driving
College of Engineering, Purdue University, West Lafayette, IN, USA · Toyota InfoTech Labs, Mountain View, CA, USA
Extraction and Analysis of Multimodal Concepts in Vision Language Models through Sparse Autoencoders
Jun 19, 2026Sergio Lanza, Jae Hee Lee, Stefan WermterVision-Language Models VLM Interpretability
Knowledge Technology, Department of Informatics, University of Hamburg, Hamburg, Germany
Beyond 'One Language, One Script': Quantifying Orthographic Bias in Multilingual VLMs with PuMVR
Jun 18, 2026Prabhjot Singh, Bhushan Pawar, Madhu ReddiboinaVLM Evaluation Vision-Language Models
RediMinds Inc., USA
The Hidden Evolution of Disguised Visual Context inside the VLM
Jun 18, 2026Wish Suharitdamrong, Tony Alex, Muhammad Awais +1Vision-Language Models Large Vision-Language Models
Surrey Institute for People-Centred AI, University of Surrey, Guildford, GU2 7XH, UK · Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK

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FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval

Zhenqi He, Ziqi Jiang, Yuanpei Liu, Yanghao Wang+2

The Hong Kong University of Science and Technology, Hong Kong SAR · The University of Hong Kong, Hong Kong SAR

Vision-Language Models Composed Image Retrieval

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Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image by editing a reference image with a natural-language instruction, without relying on domain-specific annotated triplets. Most existing ZS-CIR methods rely on textual inversion to translate the reference image into pseudo-text tokens and then compose them with the instruction via simple concatenation in the text space, which can be lossy and brittle for fine-grained semantics. In this work, we propose a new paradigm, namely FlowCIR, that casts ZS-CIR as conditional semantic transport between reference and target embeddings. Leveraging \emph{conditional flow matching}, our model learns a lightweight transport field that maps the instruction representation toward a target-aligned query embedding conditioned on the reference image. Since FlowCIR operates on pre-extracted VLM embeddings and trains only a small transport module without updating the image or text encoder, it offers a computationally efficient training protocol compared with prior textual-inversion-based approaches. The resulting framework is training-efficient, requiring roughly

10\times

fewer training resources than prior textual-inversion-based approaches. We further identify negation and removal as a major failure mode of VLM-based composition. To address this, we propose an inference-only Multi-Negative Steering strategy that steers a negation-containing relative instruction away from its negated semantics, mitigating the limited negation handling of VLMs and improving robustness on negation-heavy queries. Extensive experiments on standard CIR benchmarks demonstrate that FlowCIR achieves strong and competitive performance compared with recent ZS-CIR methods.

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