Multimodal

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Period ending 2026-09-21

65 new papers

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Period ending 2026-09-14

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Period ending 2026-09-07

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Multimodal Learning

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Cross-Modal Learning

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Multi-Modal Large Language Models

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Multimodal Reasoning

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Multimodal Benchmarks

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Unified Multimodal Models

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Cross-Modal Attention

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Input Modality

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Modality Gap

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Multimodal Generation

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Cross-Modal Alignment

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66 papersExplore

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Video Multimodal Large Language Models

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58 papersExplore

1,965 papers

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An Analysis Focused on Womens Safety: Can VAD Models Be Enhanced by a Multi-modal Dataset?
May 25, 2026Sangeeta ., Maddikuntla Sai Prajwal, Debi Prosad Dogra +4Video Anomaly Understanding Multimodal Dataset
Beyond Appearance: Can Multimodal Large Language Models Exploit Vertical Structure for Remote Sensing Natural Scene Understanding?
May 25, 2026Jing Huang, Duanchu Wang, Junjie Yang +5Remote Sensing Multi-Modal Large Language Models
CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning
May 25, 2026Sriram MandalikaCross-Modal Alignment Cross-Modal Learning
AnE: Pushing the Reasoning Frontier of Multimodal LLMs via Anchor Evolution
May 25, 2026Zehao Wang, Yihan Zeng, Zidong Gong +5Multimodal Reasoning Benchmarks Large Language Model Reasoning
StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMs
May 25, 2026Yang Luo, Xinran Liu, Tiantian Ji +3Large Language Model Safety Multi-Modal Large Language Models
MAIL++: Multi-Modal Bi-directional Agent Layer for Vision-Language Models
May 25, 2026Kaixiang Chen, Pengfei Fang, Hui XueCross-Modal Learning Multimodal Agents
BigMac: Breaking the Pareto Frontier of Compute and Memory in Multimodal LLM Training
May 25, 2026Zili Zhang, Chengxu Yang, Shenglong Zhang +8Large Models Multi-Modal Large Language Models
Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning
May 25, 2026Fanhu Zeng, Zhicong Luo, Zefan Wang +3Multimodal Reasoning Visual Reasoning
Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Driving
May 25, 2026Ruoyu Yao, Ruiguo Zhong, Pei Liu +3Autonomous Driving Efficient Vision-Language-Action Models
Can MLLMs Reason Beyond Language? VisReason: A Comprehensive Benchmark for Vision-Centric Reasoning
May 25, 2026Longteng Guo, Yifan Wang, Pengkang Huo +4Multimodal Reasoning Benchmarks Multi-Modal Large Language Models
Toward Native Multimodal Modeling: A Roadmap
May 25, 2026Siyu An, Junru Lu, Junnan Dong +18Unified Multimodal Models Cross-Modal Learning
Dual-Pathway Geometry-Aware MLLM for Spatial Intelligence
May 25, 2026Yufei Zheng, Xuhan Zhu, Zide Liu +9Multi-Modal Large Language Models 3D Perception
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
May 25, 2026Renjie Lu, Xulong Zhang, Xiaoyang Qu +2Unified Multimodal Models Inductive Bias
Mimir: Large-scale Multilingual Concept Modeling
May 24, 2026Elio Musacchio, Lucia Siciliani, Pierpaolo BasileMulti-Modal Large Language Models Next-Token Prediction
Baton: Explicit Semantic Blueprints for Joint Video-Audio Generation
May 24, 2026Shuyuan Tu, Qi Tian, Zihan Yang +9Joint Audio-Video Generation Audio Latent
SpongeBob: Sync-Aware Harmonious Audio-Visual Generative Editing
May 24, 2026Sen Liang, Cong Wang, Fengbin Guan +6Audio-Visual Consistency Video Editing
MultiHaluDet: Multilingual Hallucination Detection via LLM Hidden State Probing
May 24, 2026Riasad Alvi, Nurul Labib Sayeedi, Md. Faiyaz Abdullah SayeediRobust Hallucination Detection Multilingual Large Language Models
Zero-Shot Parkinson's Disease Detection from Speech: Comparing Large Audio and Language Models
May 24, 2026Muhammad Ashad Kabir, Sirajam MuniraParkinson Disease Detection
Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models
May 24, 2026Zhipeng Ye, Jiaqi Huang, Feng Jiang +5LLM Inference Efficiency Imagenet
DUEL: Adversarial Self-Play for Multimodal Reasoning
May 24, 2026Lin Qiu, Hanqing Zeng, Yao Liu +3Visual Reasoning Self-Play
PANDO: Efficient Multimodal AI Agents via Online Skill Distillation
May 24, 2026Yubo Li, Yidi Miao, Yuntian Shen +1Multimodal Agents Web Agents
Image-Conditioned Instance Prompt Network for Referring Remote Sensing Image Segmentation
May 23, 2026Biaoyu Ren, Qingsheng Wang, Cun Xu +2Remote Sensing Image Segmentation Remote Sensing
OmniEgo-R $^2$ : A Routed Reasoning Framework for the 1st Cross-Domain EgoCross Challenge at CVPR 2026
May 23, 2026Zixu Li, Zhiwei Chen, Zhiheng Fu +4Egocentric Video Multimodal Reasoning
Structured Visual Evidence Decomposition for Evidence-Grounded Multimodal Screening of Obstructive Sleep Apnea-Hypopnea Syndrome
May 23, 2026Chen Zhan, Yingchen Wei, Xiaoyu Tan +2Screening Multimodal Clinical Data
PGT: Procedurally Generated Tasks for improving visual grounding in MLLMs
May 22, 2026Rim Assouel, Amir Bar, Michal Drozdzal +1Explicit Visual Grounding Fine-Grained Perception
ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models
May 22, 2026Fen Wang, Zekai Shao, Qiman Kang +5Chart Multimodal Benchmarks
Representation Alignment Rests on Linear Structure
May 22, 2026Kiril Bangachev, Guy Bresler, Yury PolyanskiyLatent Representation Alignment Cross-Modal Alignment
Calibration-Informative Region Selection for Online LiDAR--Camera Calibration in Agricultural Environments
May 22, 2026Rajitha de Silva, Grzegorz CielniakLidar Camera Intrinsics
RE-TRIANGLE: Does TRIANGLE Enable Multimodal Alignment Beyond Cosine Similarity in Retrieval?
May 22, 2026Arijit Ghosh, Aritra Bandyopadhyay, Chiranjeev Bindra +1Multimodal Alignment Multimodal Retrieval
Understanding Privacy by Formalizing It
May 22, 2026Réka Markovich, Truls Pedersen, Marija SlavkovikAI Privacy Risks and Protection Social Norms
Balancing Multimodal Learning through Label Space Reshaping
May 22, 2026Xiaoyu Ma, Weijie Zhang, Yuanhao Gao +3Robust Multimodal Learning Modality Gap
CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
May 22, 2026Xiaoyi Huang, Kejia Zhang, Zhiming LuoLarge Vision Language Models Contrastive Decoding
Emotion Recognition in Sign Language Conversation
May 22, 2026Yusong Wang, Keyu Mao, Takao Obi +2Sign Language Emotion Recognition
Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey
May 22, 2026Liangwei Nathan Zheng, Wei Emma Zhang, Olaf Maennel +2Robust Multimodal Learning Mixture-of-Experts Models
Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes
May 22, 2026Wenxuan Peng, Bharath Hariharan, Hadar Averbuch-ElorLarge-Scale Image Generation Indoor Scene Generation
Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs
May 22, 2026Casey Ford, Madison Van Doren, Sicheng Jin +1Large Language Model Jailbreaks Multilingual Safety
STAMBRIDGE: Spectral-Temporal Amplitude-aware Mid-Feature Bridge for EEG Visual Decoding
May 22, 2026Jiahe Meng, Weiming Zeng, Yueyang Li +5Modality Gap
Inconsistency-aware Multimodal Schrödinger Bridge for Deepfake Localization
May 22, 2026Jiayu Xiong, Jing Wang, Qi Zhang +2Explainable Deepfake Detection Deepfake Detection
RoboSurg-VQA: A Multimodal Benchmark for Surgical Segmentation-Aware Visual Question Answering
May 21, 2026Chengyi Zhang, Zi Ye, Ziyang WangKnowledge-Based Visual Question Answering Textvqa
Uncovering the Latent Potential of Deep Intermediate Representations
May 21, 2026Arnesh Batra, Arush Gumber, Aniket Khandelwal +2Geometric Deep Learning Transformer Layers
SceneAligner: 3D-Grounded Floorplan Localization in the Wild
May 21, 2026Junhyeong Cho, Ruojin Cai, Hadar Averbuch-ElorFloor Plan Generation Robust Localization
SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation
May 21, 2026Xiaolong Zhou, Yifei Liu, Ziyang Gong +8Embodied Spatial Intelligence Visual Degradation
Understanding Multimodal Failure in Action-Chunking Behavioral Cloning
May 21, 2026Lorenzo Mazza, Massimiliano Datres, Ariel Rodriguez +3Behavior Cloning Unified Multimodal Models
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
AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculture
May 21, 2026Zi Ye, Yibin Wen, Xiaoya Fan +10Multimodal Agents Agricultural Landscapes
Bernini: Latent Semantic Planning for Video Diffusion
May 21, 2026Bernini Team, Chenchen Liu, Junyi Chen +9Video Multimodal Large Language Models Rotary Position Embedding
Enhancing Multimodal Large Language Models for Safety-Critical Driving Video Analysis
May 21, 2026Tomaso Trinci, Henrique Piñeiro Monteagudo, Leonardo TaccariVideo Multimodal Large Language Models Multi-Modal Large Language Models
Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles
May 21, 2026Jinyang Wu, Guocheng Zhai, Ruihan Jin +7Multi-Modal Large Language Models Multimodal Agents
Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?
May 21, 2026Luca Modica, Filip Landin, Mehrdad Farahani +3Multi-Modal Large Language Models Factual Recall
Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability
May 21, 2026Joël Roman Ky, Salah Ghamizi, Maxime CordyCross-Modal Learning Unimodal Representations
One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems
May 21, 2026Yufei Shi, Weilong Yan, Naixuan Huang +5Multi-Agent Systems Cross-Modal Learning
Faithful-MR1: Faithful Multimodal Reasoning via Anchoring and Reinforcing Visual Attention
May 21, 2026Changyuan Tian, Zhicong Lu, Huaxing Liu +7Multimodal Reasoning Multimodal Learning
Distributed Image Compression with Multimodal Side Information at Extremely Low Bitrates
May 21, 2026Guojun Xu, Mingyang Zhang, Jianwen Xiang +3Learned Image Compression Ultra-Low Bitrates
AgroVG: A Large-Scale Multi-Source Benchmark for Agricultural Visual Grounding
May 21, 2026Haocheng Li, Juepeng Zheng, Zenghao Yang +5Agricultural Landscapes Visual Grounding
LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning
May 21, 2026Yifan Dai, Zhenhua Wu, Bohan Zeng +18Audio-Visual Reasoning Omni-Modal
Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow
May 21, 2026Chengsheng Zhang, Chenghao Sun, Zhining Xie +1Large Vision Language Models Particular Emotion-Aware Response
Video as Natural Augmentation: Towards Unified AI-Generated Image and Video Detection
May 21, 2026Zhengcen Li, Chenyang Jiang, Liangxu Su +4Ai-Generated Image Detection Machine-Generated Text Detection
MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues
May 21, 2026Dazhao Du, Liao Duan, Jian Liu +5Video Temporal Grounding Temporal Grounding
Two-Stage Multimodal Framework for Emotion Mimicry Intensity Prediction
May 21, 2026Dinithi Dissanayake, Shaveen Silva, Ovindu Atukorala +2Emotion Recognition Modality-Specific Encoders
BEiTScore: Reference-free Image Captioning Evaluation with an Efficient Cross-Encoder Model
May 20, 2026Gonçalo Gomes, Bruno Martins, Chrysoula ZervaRemote Sensing Image Change Captioning Video Captioning

May 25, 2026 · cs.CVJ/K move · Enter open · S save

An Analysis Focused on Womens Safety: Can VAD Models Be Enhanced by a Multi-modal Dataset?

Sangeeta ., Maddikuntla Sai Prajwal, Debi Prosad Dogra, Kamalakar Vijay Thakare+3

Indian Institute of Technology Bhubaneswar Bhubaneswar, Odisha 752050, India · Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology Seoul 02792, Republic of Korea · Yonsei-KIST Convergence Research Institute, Yonsei University Seoul 03722, Republic of Korea

Women's safety and security are paramount for a modern society. Crimes against women occur in daylight as well as in low-light conditions. Often, such events are captured through real-world surveillance cameras that operate at lower resolutions. Despite substantial progress in CV-related research, video anomaly detection (VAD) focused on women's safety has not yet been adequately addressed. Existing video anomaly datasets contain well-lit, high-resolution, close-shot videos, and fail to represent women-centric anomalies such as chain snatching, stalking, inappropriate touch, and other subtle forms of crime against women. To address these problems, we propose the ExtrAnom dataset, a new multi-modal benchmark containing 1001 videos with textual descriptions, 500 normal and 501 anomalous, classified into 5 different types of women-centric crimes. The dataset comprises low-light (8%), low-resolution videos (13%), long-shot (15%), along with daylight (64%) anomalous videos. And it covers anomalous events like stalking (3.9%), chain snatching (17.6%), kidnapping (7.3%), assassinations (2.3%), harassment (18.9%), and normal (50%). Each video is supplemented with 4 textual annotations, including one human-generated and three LLM-generated descriptions, enabling cross-modal and VLM-based validations. The aim of creating a women-centric dataset is to accurately detect the women-centric anomaly patterns, which are possible to observe visually. The dataset supplements the VLMs to accurately generate video-level descriptions. ExtrAnom has been benchmarked against popular unimodal and multi-modal VAD datasets (e.g., XD-Violence, UCF-Crime, and UCA) and SOTA methods. Experiments reveal that the existing datasets are insufficient to train models for detecting women-centric anomalies.

Video Anomaly Understanding Multimodal Dataset Video Dataset Cross-Modal Learning Safety

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