82 citations · 176 across the 19 of their papers we have counts for
19 papers
Learning Transferable Temporal Primitives for Video Reasoning via Synthetic Videos
Songtao Jiang, Sibo Song, Chenyi Zhou +12
The transition from image to video understanding requires vision-language models (VLMs) to shift from recognizing static patterns to reasoning over temporal dynamics such as motion…
Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
Mingxin Li, Yanzhao Zhang, Dingkun Long +9
In this report, we introduce the Qwen3-VL-Embedding and Qwen3-VL-Reranker model series, the latest extensions of the Qwen family built on the Qwen3-VL foundation model. Together, t…
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
Songtao Jiang, Yuan Wang, Sibo Song +22
Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…
Revisiting Multimodal Positional Encoding in Vision-Language Models
Jie Huang, Xuejing Liu, Sibo Song +4
Multimodal position encoding is essential for vision-language models, yet there has been little systematic investigation into multimodal position encoding. We conduct a comprehensi…
Knowing or Guessing? Robust Medical Visual Question Answering via Joint Consistency and Contrastive Learning
Songtao Jiang, Yuxi Chen, Sibo Song +5
In high-stakes medical applications, consistent answering across diverse question phrasings is essential for reliable diagnosis. However, we reveal that current Medical Vision-Lang…
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making
Songtao Jiang, Yuan Wang, Ruizhe Chen +8
In medical visual question answering (Med-VQA), achieving accurate responses relies on three critical steps: precise perception of medical imaging data, logical reasoning grounded…
OmniV-Med: Scaling Medical Vision-Language Model for Universal Visual Understanding
Songtao Jiang, Yuan Wang, Sibo Song +6
The practical deployment of medical vision-language models (Med-VLMs) necessitates seamless integration of textual data with diverse visual modalities, including 2D/3D images and v…
Generative Compositor for Few-Shot Visual Information Extraction
Zhibo Yang, Wei Hua, Sibo Song +4
Visual Information Extraction (VIE), aiming at extracting structured information from visually rich document images, plays a pivotal role in document processing. Considering variou…
Qwen2.5-VL Technical Report
Shuai Bai, Keqin Chen, Xuejing Liu +24
We introduce Qwen2.5-VL, the latest flagship model of Qwen vision-language series, which demonstrates significant advancements in both foundational capabilities and innovative func…
OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models
Wenwen Yu, Zhibo Yang, Jianqiang Wan +5
Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understanding and the emergence of large language…
OmniParser: A Unified Framework for Text Spotting, Key Information Extraction and Table Recognition
Jianqiang Wan, Sibo Song, Wenwen Yu +6
Recently, visually-situated text parsing (VsTP) has experienced notable advancements, driven by the increasing demand for automated document understanding and the emergence of Gene…
Modeling Entities as Semantic Points for Visual Information Extraction in the Wild
Zhibo Yang, Rujiao Long, Pengfei Wang +5
Recently, Visual Information Extraction (VIE) has been becoming increasingly important in both the academia and industry, due to the wide range of real-world applications. Previous…
Vision-Language Pre-Training for Boosting Scene Text Detectors
Sibo Song, Jianqiang Wan, Zhibo Yang +4
Recently, vision-language joint representation learning has proven to be highly effective in various scenarios. In this paper, we specifically adapt vision-language joint learning…
Deep Adaptive Temporal Pooling for Activity Recognition
Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar +1
Deep neural networks have recently achieved competitive accuracy for human activity recognition. However, there is room for improvement, especially in modeling long-term temporal i…
Defense Against Adversarial Attacks with Saak Transform
Sibo Song, Yueru Chen, Ngai-Man Cheung +1
Deep neural networks (DNNs) are known to be vulnerable to adversarial perturbations, which imposes a serious threat to DNN-based decision systems. In this paper, we propose to appl…
Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
Zhe Wang, Kingsley Kuan, Mathieu Ravaut +13
The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% o…
On Classification of Distorted Images with Deep Convolutional Neural Networks
Yiren Zhou, Sibo Song, Ngai-Man Cheung
Image blur and image noise are common distortions during image acquisition. In this paper, we systematically study the effect of image distortions on the deep neural network (DNN)…
Egocentric Activity Recognition with Multimodal Fisher Vector
Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar +2
With the increasing availability of wearable devices, research on egocentric activity recognition has received much attention recently. In this paper, we build a Multimodal Egocent…