34 citations · 41 across the 10 of their papers we have counts for
10 papers
CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization
Seohyeon Cha, Huancheng Chen, Dongjun Kim +4
Post-training quantization (PTQ) enables efficient deployment of large language models by mapping pretrained weights to low-bit formats without retraining, typically using a small…
Explainable AI as a Double-Edged Sword in Dermatology: The Impact on Clinicians versus The Public
Xuhai Xu, Haoyu Hu, Haoran Zhang +21
Artificial intelligence (AI) is increasingly permeating healthcare, from physician assistants to consumer applications. Since AI algorithm's opacity challenges human interaction, e…
LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology
Zhenyue Qin, Yang Liu, Yu Yin +13
Vision-threatening eye diseases pose a major global health burden, with timely diagnosis limited by workforce shortages and restricted access to specialized care. While multimodal…
Towards Vision Mixture of Experts for Wildlife Monitoring on the Edge
Emmanuel Azuh Mensah, Anderson Lee, Haoran Zhang +2
The explosion of IoT sensors in industrial, consumer and remote sensing use cases has come with unprecedented demand for computing infrastructure to transmit and to analyze petabyt…
Curriculum Prompting Foundation Models for Medical Image Segmentation
Xiuqi Zheng, Yuhang Zhang, Haoran Zhang +4
Adapting large pre-trained foundation models, e.g., SAM, for medical image segmentation remains a significant challenge. A crucial step involves the formulation of a series of spec…
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole +4
Large repositories of image-caption pairs are essential for the development of vision-language models. However, these datasets are often extracted from noisy data scraped from the…
Multimodal Information Interaction for Medical Image Segmentation
Xinxin Fan, Lin Liu, Haoran Zhang
The use of multimodal data in assisted diagnosis and segmentation has emerged as a prominent area of interest in current research. However, one of the primary challenges is how to…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Tokenization Is More Than Compression
Craig W. Schmidt, Varshini Reddy, Haoran Zhang +4
Tokenization is a foundational step in natural language processing (NLP) tasks, bridging raw text and language models. Existing tokenization approaches like Byte-Pair Encoding (BPE…
OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
Jinhui Yuan, Xinqi Li, Cheng Cheng +9
Deep learning frameworks such as TensorFlow and PyTorch provide a productive interface for expressing and training a deep neural network (DNN) model on a single device or using dat…