no code implementations • 5 Mar 2024 • Gang Liu, Hongyang Li, Zerui He, Shenjun Zhong
In this paper, we introduce a method that incorporates gradient-guided parameter perturbations to the visual encoder of the multimodality model during both pre-training and fine-tuning phases, to improve model generalization for downstream medical VQA tasks.
1 code implementation • 5 Jan 2024 • Gang Liu, Jinlong He, Pengfei Li, Genrong He, Zhaolin Chen, Shenjun Zhong
In this paper, we propose a parameter efficient framework for fine-tuning MLLMs, specifically validated on medical visual question answering (Med-VQA) and medical report generation (MRG) tasks, using public benchmark datasets.
Ranked #1 on Medical Visual Question Answering on VQA-RAD (using extra training data)
Medical Report Generation Medical Visual Question Answering +4
1 code implementation • 11 Jul 2023 • Pengfei Li, Gang Liu, Jinlong He, Zixu Zhao, Shenjun Zhong
Medical visual question answering (VQA) is a challenging task that requires answering clinical questions of a given medical image, by taking consider of both visual and language information.
Ranked #1 on Medical Visual Question Answering on PathVQA
2 code implementations • 24 Nov 2022 • Pengfei Li, Gang Liu, Lin Tan, Jinying Liao, Shenjun Zhong
Medical image visual question answering (VQA) is a task to answer clinical questions, given a radiographic image, which is a challenging problem that requires a model to integrate both vision and language information.
Ranked #1 on Medical Visual Question Answering on SLAKE-English
no code implementations • 11 Jun 2021 • Kristen Moore, Shenjun Zhong, Zhen He, Torsten Rudolf, Nils Fisher, Brandon Victor, Neha Jindal
In this paper we present the results of our experiments in training and deploying a self-supervised retrieval-based chatbot trained with contrastive learning for assisting customer support agents.
2 code implementations • 8 Oct 2017 • Lisandro Kaunitz, Shenjun Zhong, Javier Kreiner
The online sports gambling industry employs teams of data analysts to build forecast models that turn the odds at sports games in their favour.
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