Large Vision Language Models

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Toward Semantic-Agnostic and Shape-Aware Vision-Language Segmentation Models
May 27, 2026Corentin Seutin, Mohamed Amine Ettaki, Michaël Clément +2Large Vision Language Models Segmentation Model
ProgVLA: Progress-Aware Robot Manipulation Skill Learning
May 27, 2026Seungsu Kim, Jinyoung Choi, Seungmin Baek +1Generalizable Robotic Manipulations Large Vision Language Models
Look on Demand: A Cognitive Scheduling Framework for Visual Evidence Acquisition in Multimodal Reasoning
May 27, 2026Yang Zhang, Xiaoshuai Sun, Rui Zhao +5Multimodal Reasoning Multimodal Reasoning Benchmarks
Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models
May 27, 2026Haozhan Shen, Tiancheng Zhao, Kangjia Zhao +1Ava-Vlm Vision-Language
Risk-aware Selective Prompting for Hallucination Mitigation in Large Vision-Language Models
May 27, 2026Yuang Huang, Yafeng Zhang, Yu ZilanLarge Language Model Hallucination Large Vision Language Models
CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models
May 27, 2026Fengze Yang, Bo Yu, Xuewen Luo +2Large Vision Language Models Vision Encoders
Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models
May 27, 2026Landi He, Mingde Yao, Shawn Young +1Visual Token Pruning Large Vision Language Models
ABot-OCR Technical Report
May 27, 2026Kaitao Jiang, Ruiyan Gong, Xiaolong Cheng +3Deepseek-Ocr Large Vision Language Models
Evolving to the Aesthetics of a Vision-Language Model
May 27, 2026Stephen James Krol, Jon McCormackAesthetics Vision-Language
Structure-Guided Visual Perturbation Neutralization for LVLMs
May 27, 2026Yuanhe Zhang, Xueting Wang, YanBin Ren +6Large Vision Language Models Perceptual Quality
LAST: Bridging Vision-Language and Action Manifolds via Gromov-Wasserstein Alignment
May 27, 2026Huaihai Lyu, Chaofan Chen, Yuheng Ji +4Vision-Language-Action Models Vision-Language
Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
May 27, 2026Yuting Ma, Lechao Cheng, Xiaohua XuFederated Learning Vision-Language Model Adaptation
EdgeFlow: Edge-Map Augmented VLM-Based Flowchart Processing for Industrial Requirements Engineering
May 26, 2026Zhifei Dou, Shabnam Hassani, Ou WeiDiagrams Ava-Vlm
Real Images, Worse Judgments: Evaluating Vision-Language Models on Concreteness and Imagery
May 26, 2026Yifan Jiang, Ruoxi Ning, Sheng Yao +1Large Vision Language Models Representational Adaptation
Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models
May 26, 2026Yifan Jiang, Dae Yon Hwang, Jesse C. Cresswell +1Chart Visual Reasoning
Self-Ensembling Vision-Language Models for Chart Data Extraction
May 26, 2026Thomas Berkane, Qianyi Wang, Maimuna S. MajumderChart Tabular Data
Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models
May 26, 2026Aaron Branson Cigres Li, Zhaowei Wang, Yu Zhao +9Multimodal Retrieval Large Vision Language Models
Leveraging Visual Signals for Robust Token-Level Uncertainty in Vision-Language Generation
May 26, 2026Joseph Hoche, David Brellmann, Gianni FranchiLarge Vision Language Models Large Language Model Uncertainty
CodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning
May 26, 2026Zihan Lin, Songhe Deng, Shuwei He +6Video Captioning Vision Encoders
METATR: A Multilingual, Evolving Benchmark for Automatic Text Recognition
May 26, 2026Mélodie Boillet, Solène Tarride, Christopher KermorvantMultilingual Benchmark Multilingual
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
May 26, 2026Yuanwei Hu, Bo Peng, Yadan Luo +3Out-Of-Distribution Detection Large Vision Language Models
FTibSuite: A Comprehensive Resource Suite for Tibetan Vision-Language Modeling
May 26, 2026Guixian Xu, Yide Liang, Zeli Su +5Large Vision Language Models Multimodal Benchmarks
A Hybrid Vision-Language Architecture for Automated Defect Reasoning and Report Generation in Industrial Inspection
May 26, 2026Malikussaid, Imad GoharInspection Large Vision Language Models
InterSketch: An Interleaved Reasoning Model with Self-correcting Visual Sketch and Stepwise Reward
May 26, 2026Zhiwei Ning, Wenwen Tong, Xiangli Kong +12Large Vision Language Models Sketches
Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization
May 26, 2026Xiang Fang, Wanlong Fang, Changshuo WangLarge Vision Language Models Cross-Modal Learning
OmniGF: A Dual-Branch Vision-Language Framework for Unified Gaze Following
May 26, 2026Qiaomu Miao, Haoyu Wu, Jingyi Xu +2Gaze Target Estimation Large Vision Language Models
BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma
May 25, 2026Junlin Yang, Tian Yu, Nicha C. Dvornek +6Cholangiocarcinoma Experts
Stateful Inference for Low-Latency Multi-Agent Tool Calling
May 25, 2026Victor NorgrenTool Low-Latency Systems
DRScaffold: Boosting Dense-Scene Reasoning in Lightweight Vision Language Models
May 25, 2026Xinrui Shi, Kai Liu, Ziqing Zhang +3Large Vision Language Models Scene Representation
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence
May 25, 2026Xiang An, Yin Xie, Feilong Tang +27Video Understanding Vision Encoders
RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing
May 25, 2026Sofiat Abioye, Ufaq Khan, Shazad Ashraf +4Medical Vision-Language Models Colorectal Cancer
[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation
May 25, 2026Akang Wang, Xili Deng, Zhanxuan Hu +3Vision-Language Vision Encoders
Rethinking VLM Representation for VLA Initialization
May 25, 2026Weifeng Lin, Siyuan Huang, Hao Li +5Vision-Language-Action Models Vision-Language
CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning
May 25, 2026Sriram MandalikaCross-Modal Alignment Cross-Modal Learning
Back to Parsimonious Latents: Learning Task-Centric World Models from Visual Foundations
May 25, 2026Minghao Fu, Fan Feng, Nicklas Hansen +1World Models Frozen Vision-Language Models
Adversarial Orthogonal Disentanglement for LVLM Hallucination Mitigation
May 25, 2026Ruoxi Cheng, Haoxuan Ma, Zhengfei Hai +6Large Language Model Hallucination Large Vision Language Models
Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent
May 24, 2026Takato YasunoLarge Vision Language Models Structural Damage
Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
May 24, 2026Yangneng Chen, Jing LiLarge Vision Language Models Mitigation
Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration
May 24, 2026Yuanzhi Xu, Qian Gao, Jun Fan +4Large Vision Language Models Hallucination Mitigation
Interpretability Transfer from Language to Vision via Sparse Autoencoders
May 24, 2026Alexey Kravets, Da Li, Chuan Li +2Large Vision Language Models Improving Sparse Autoencoders
Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering
May 24, 2026Ojonugwa Oluwafemi Ejiga Peter, Frederick Akor Ejiga, Fahmi Khalifa +1Video Capsule Endoscopy Medical Image Generation
PEDESTRIANQA: A Benchmark for Vision-Language Models on Pedestrian Intention and Trajectory Prediction
May 23, 2026Naman Mishra, Shankar Gangisetty, C. V. JawaharPedestrian Trajectory Prediction Large Vision Language Models
MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding
May 23, 2026Zexuan Chen, Sichao Liu, Runhao Lu +4Electroencephalography Spatial Super-Resolution Neural Recordings
VectorArk: Learning Practical Image Vectorization with Rounded Polygon Representation
May 23, 2026Tarun Gehlaut, Difan Liu, Charu Bansal +5Scalable Vector Graphic Large Vision Language Models
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
May 22, 2026Christian Gumbsch, Leonardo Barcellona, Lennard Schünemann +7Scalable Robot Learning Large Vision Language Models
Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models
May 22, 2026Bo Peng, Jie Lu, Guangquan Zhang +1Out-Of-Distribution Detection Positive--Unlabeled Learning
CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
May 22, 2026Xiaoyi Huang, Kejia Zhang, Zhiming LuoLarge Vision Language Models Contrastive Decoding
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving
May 22, 2026Hao Vo, Khoa Vo, Phu Loc Nguyen +10Autonomous Driving Large Vision Language Models
MotiMotion: Motion-Controlled Video Generation with Visual Reasoning
May 21, 2026Lee Hsin-Ying, Hanwen Jiang, Yiqun Mei +3Visual Reasoning Large Vision Language Models
AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation
May 21, 2026Wenxuan Guo, Xiuwei Xu, Yichen Liu +7Vision-Language Navigation Large Vision Language Models
Seeing without Looking: Do Vision-Language Benchmarks Really Test Vision?
May 21, 2026Zixuan Lan, Luzhe Sun, Matthew R. Walter +1Large Vision Language Models Explicit Visual Grounding
Transcoders Trace Visual Grounding and Hallucinations in Vision-Language Models
May 21, 2026Dimitrios Damianos, Leon Voukoutis, Georgios Skyrianos +2Large Vision Language Models Hallucinations
Conceptualizing Embeddings: Sparse Disentanglement for Vision-Language Models
May 21, 2026Piotr Kubaty, Patryk Marszałek, Łukasz Struski +3Multimodal Embeddings Vision-Language
What Does the Caption Really Say? Counterfactual Phrase Intervention for Compositional Data Selection in Vision-Language Pretraining
May 21, 2026Hyejin Go, Semi Lee, Hyesong ChoiImage-Text Pairs Video Captioning
Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
May 21, 2026Ruofan Jin, Zaixi ZhangVision-Language-Action Models Vision-Language Model Adaptation
Rethinking Noise-Robust Training for Frozen Vision Foundation Models: A Cross-Dataset Benchmark with a Case Study of Small-Loss Failure
May 21, 2026Zitong Li, Haoyu WangNoisy Labels Noise-Aware
Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling
May 21, 2026David Méndez, Roberto Confalonieri, Natalia Díaz RodríguezVision-Language Alignment Cross-Modal Learning
Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability
May 21, 2026Xiang Chen, Yuxian Dong, Chao Li +6Large Vision Language Models Infrared
JMed48k: A Multi-Profession Japanese Medical Licensing Benchmark for Vision-Language Model Evaluation
May 21, 2026Yue Xun, Junyu Liu, Qian Niu +10Medical Visual Question Answering Examiners
COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition
May 21, 2026Junhyub Lee, Seunghun Chae, Hyosu KimLarge Vision Language Models Visual Representations

May 27, 2026 · cs.CVJ/K move · Enter open · S save

Toward Semantic-Agnostic and Shape-Aware Vision-Language Segmentation Models

Corentin Seutin, Mohamed Amine Ettaki, Michaël Clément, Pierrick Coupé+1

Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800, France · Univ. Bordeaux, CNRS, Bordeaux INP, IMS, UMR 5218, France

Vision-language segmentation models have recently achieved strong performance by leveraging high-level semantic object categories expressed in natural language. However, this semantic dependence limits their ability to reason about intrinsic visual properties such as shape, geometry, or texture, which are essential in many real-world applications. In this work, we introduce Semantic-Agnostic aNd Shape-Aware (SANSA) segmentation, a new paradigm that requires segmentation models to operate solely from non-semantic textual descriptions. To this end, we propose two strategies to generate SANSA segmentation prompts based on either dictionary constraints or example guidance, both generating semantic-agnostic textual descriptions. These prompts are then used to finetune segmentation models under semantic-agnostic supervision. Experiments show that finetuning on SANSA prompts yields up to a 20% mIoU improvement on this new segmentation task, compared to pretrained state-of-the-art models, while maintaining strong performance on standard semantic prompts. These results highlight the importance of low- and mid-level visual reasoning for improving the generalization and controllability of vision-language segmentation models.

Large Vision Language Models Segmentation Model Vision-Language Visual Reasoning Natural Language Descriptions

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