1 citations · 1 across the 5 of their papers we have counts for
5 papers
Detached Skip-Links and -Probe: Decoupling Feature Aggregation from Gradient Propagation for MLLM OCR
Ziye Yuan, Ruchang Yao, Chengxin Zheng +3
Multimodal large language models (MLLMs) excel at high-level reasoning yet fail on OCR tasks where fine-grained visual details are compromised or misaligned. We identify an overloo…
Qianfan-VL: Domain-Enhanced Universal Vision-Language Models
Daxiang Dong, Mingming Zheng, Dong Xu +32
We present Qianfan-VL, a series of multimodal large language models ranging from 3B to 70B parameters, achieving state-of-the-art performance through innovative domain enhancement…
HSENet: Hybrid Spatial Encoding Network for 3D Medical Vision-Language Understanding
Yanzhao Shi, Xiaodan Zhang, Junzhong Ji +4
Automated 3D CT diagnosis empowers clinicians to make timely, evidence-based decisions by enhancing diagnostic accuracy and workflow efficiency. While multimodal large language mod…
MEPNet: Medical Entity-balanced Prompting Network for Brain CT Report Generation
Xiaodan Zhang, Yanzhao Shi, Junzhong Ji +2
The automatic generation of brain CT reports has gained widespread attention, given its potential to assist radiologists in diagnosing cranial diseases. However, brain CT scans inv…
See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning
Chengxin Zheng, Junzhong Ji, Yanzhao Shi +2
Brain CT report generation is significant to aid physicians in diagnosing cranial diseases. Recent studies concentrate on handling the consistency between visual and textual pathol…