MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

1 code implementation • 6 Feb 2024 • Xiangxiang Chu, Limeng Qiao, Xinyu Zhang, Shuang Xu, Fei Wei, Yang Yang, Xiaofei Sun, Yiming Hu, Xinyang Lin, Bo Zhang, Chunhua Shen

We introduce MobileVLM V2, a family of significantly improved vision language models upon MobileVLM, which proves that a delicate orchestration of novel architectural design, an improved training scheme tailored for mobile VLMs, and rich high-quality dataset curation can substantially benefit VLMs' performance.

AutoML Language Modelling

MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

1 code implementation • 28 Dec 2023 • Xiangxiang Chu, Limeng Qiao, Xinyang Lin, Shuang Xu, Yang Yang, Yiming Hu, Fei Wei, Xinyu Zhang, Bo Zhang, Xiaolin Wei, Chunhua Shen

We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices.

AutoML Language Modelling

Federated Learning with Positive and Unlabeled Data

1 code implementation • 21 Jun 2021 • Xinyang Lin, Hanting Chen, Yixing Xu, Chao Xu, Xiaolin Gui, Yiping Deng, Yunhe Wang

We study the problem of learning from positive and unlabeled (PU) data in the federated setting, where each client only labels a little part of their dataset due to the limitation of resources and time.

Federated Learning

Location Privacy Protection in Online Query based on Privacy Region Replacement

no code implementations • 6 Jan 2020 • Yali JI, Ruowei GUI, Xiaolin Gui, Dong LIAO, Xinyang Lin

In order to realize online location query based on Privacy in the location-based service (LBS), a location privacy protection method based on privacy region replacement (PRR) was proposed to improve the query response time without reducing the degree of privacy protection in this paper.