no code implementations • 24 Feb 2024 • Haotian Xia, Zhengbang Yang, Yuqing Wang, Rhys Tracy, Yun Zhao, Dongdong Huang, Zezhi Chen, Yan Zhu, Yuan-Fang Wang, Weining Shen
A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP).
no code implementations • 1 Feb 2024 • Yuqing Wang, Malvika Pillai, Yun Zhao, Catherine Curtin, Tina Hernandez-Boussard
In the high-stakes realm of healthcare, ensuring fairness in predictive models is crucial.
1 code implementation • 29 Dec 2023 • Yuqing Wang, Yun Zhao
To address this gap, our study undertakes a thorough evaluation of Gemini's performance in complex reasoning tasks that necessitate the integration of commonsense knowledge across modalities.
1 code implementation • 2 Oct 2023 • Yuqing Wang, Yun Zhao
In this paper, we introduce TRAM, a temporal reasoning benchmark composed of ten datasets, encompassing various temporal aspects of events such as order, arithmetic, frequency, and duration, designed to facilitate a comprehensive evaluation of the temporal reasoning capabilities of large language models (LLMs).
1 code implementation • 26 Sep 2023 • Haotian Xia, Rhys Tracy, Yun Zhao, Yuqing Wang, Yuan-Fang Wang, Weining Shen
Our frameworks combine setting ball trajectory recognition with a novel set trajectory classifier to generate comprehensive and advanced statistical data.
1 code implementation • 10 Aug 2023 • Yuqing Wang, Yun Zhao
This study underscores the potential to amplify the understanding abilities of LLMs and highlights the benefits of mirroring human introspective reasoning in NLU tasks.
no code implementations • 10 May 2023 • Yuqing Wang, Yun Zhao, Linda Petzold
The Segment Anything Model (SAM) is a foundation model for general image segmentation.
1 code implementation • 9 Apr 2023 • Yuqing Wang, Yun Zhao, Linda Petzold
In this study, we conduct a comprehensive evaluation of state-of-the-art LLMs, namely GPT-3. 5, GPT-4, and Bard, within the realm of clinical language understanding tasks.
no code implementations • 20 Jan 2023 • Yueyang Liu, Artemio Soto-Breceda, Yun Zhao, Phillipa Karoly, Mark J. Cook, David B. Grayden, Daniel Schmidt, Levin Kuhlmann1
Approach An LSTM filter was trained on simulated EEG data generated by a neural mass model using a wide range of parameters.
no code implementations • 28 Sep 2022 • Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang, Linda Petzold
The second goal is to introduce a volleyball descriptive language to fully describe the rally processes in the games and apply the language to our dataset.
no code implementations • 26 Sep 2022 • Yun Zhao, Hang Chen, Min Lin, Haiou Zhang, Tao Yan, Xing Lin, Ruqi Huang, Qionghai Dai
Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance.
no code implementations • 26 Jun 2022 • Yuqing Wang, Yun Zhao, Linda Petzold
As critically ill patients frequently develop anemia or coagulopathy, transfusion of blood products is a frequent intervention in the Intensive Care Units (ICU).
no code implementations • 28 Mar 2022 • Yuqing Wang, Yun Zhao, Linda Petzold
Most current multivariate time series (MTS) classification algorithms focus on improving the predictive accuracy.
no code implementations • 28 Mar 2022 • Yuqing Wang, Yun Zhao, Rachael Callcut, Linda Petzold
In this paper, we propose a multimodal Transformer model for early sepsis prediction, using the physiological time series data and clinical notes for each patient within $36$ hours of ICU admission.
no code implementations • 1 Oct 2021 • Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda Petzold
In this paper, we perform quantitative analysis of COVID-19 forecasting of confirmed cases and deaths across different regions in the United States with different forecasting horizons, and evaluate the relative impacts of the following three dimensions on the predictive performance (improvement and variation) through different evaluation metrics: model selection, hyperparameter tuning, and the length of time series required for training.
no code implementations • 24 Sep 2021 • Qizhi Zhang, Sijun Tan, Lichun Li, Yun Zhao, Dong Yin, Shan Yin
Finally, we introduce Morse-STF, an end-to-end privacy-preserving system for machine learning training that leverages all these improved protocols.
no code implementations • 22 Jun 2021 • Xinlu Zhang, Yun Zhao, Rachael Callcut, Linda Petzold
Multiple organ failure (MOF) is a severe syndrome with a high mortality rate among Intensive Care Unit (ICU) patients.
no code implementations • 26 Mar 2021 • Yun Zhao, Xuerui Yang, Jinchao Wang, Yongyu Gao, Chao Yan, Yuanfu Zhou
Although automatic speech recognition (ASR) systems achieved significantly improvements in recent years, spoken language recognition error occurs which can be easily spotted by human beings.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 19 Mar 2021 • Yun Zhao, Qinghang Hong, Xinlu Zhang, Yu Deng, Yuqing Wang, Linda Petzold
However, there is a lack of deep learning methods that can model the relationship between measurements, clinical notes and mortality outcomes.
no code implementations • 19 Mar 2021 • Yuqing Wang, Yun Zhao, Rachael Callcut, Linda Petzold
However, blindly pursuing complex classifiers is unwise as it also brings the risk of greater performance variation.
no code implementations • 22 Sep 2020 • Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, Linda Petzold
Chronic pain is defined as pain that lasts or recurs for more than 3 to 6 months, often long after the injury or illness that initially caused the pain has healed.
no code implementations • 6 Sep 2019 • Yun Zhao
Relation extraction models suffer from limited qualified training data.
no code implementations • 5 Jun 2019 • Yun Zhao, Elmer Guzman, Morgane Audouard, Zhuowei Cheng, PaulK. Hansma, Kenneth S. Kosik, Linda Petzold
In this paper, we address the problem of classifying in vitro MEA recordings of mouse and human neuronal cultures from different genotypes, where there is no easy way to directly utilize raw sequences as inputs to train an end-to-end classification model.
Cultural Vocal Bursts Intensity Prediction General Classification