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of 158
pro vyhledávání: '"Han, William"'
With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more multimodal, the utility of watermarking techniques becomes even more cri
Externí odkaz:
http://arxiv.org/abs/2406.03728
Autor:
Qiu, Jielin, Han, William, Wang, Winfred, Yang, Zhengyuan, Li, Linjie, Wang, Jianfeng, Faloutsos, Christos, Li, Lei, Wang, Lijuan
Open-domain real-world entity recognition is essential yet challenging, involving identifying various entities in diverse environments. The lack of a suitable evaluation dataset has been a major obstacle in this field due to the vast number of entiti
Externí odkaz:
http://arxiv.org/abs/2403.12339
Autor:
Jeong, Hyewon, Jabbour, Sarah, Yang, Yuzhe, Thapta, Rahul, Mozannar, Hussein, Han, William Jongwon, Mehandru, Nikita, Wornow, Michael, Lialin, Vladislav, Liu, Xin, Lozano, Alejandro, Zhu, Jiacheng, Kocielnik, Rafal Dariusz, Harrigian, Keith, Zhang, Haoran, Lee, Edward, Vukadinovic, Milos, Balagopalan, Aparna, Jeanselme, Vincent, Matton, Katherine, Demirel, Ilker, Fries, Jason, Rashidi, Parisa, Beaulieu-Jones, Brett, Xu, Xuhai Orson, McDermott, Matthew, Naumann, Tristan, Agrawal, Monica, Zitnik, Marinka, Ustun, Berk, Choi, Edward, Yeom, Kristen, Gursoy, Gamze, Ghassemi, Marzyeh, Pierson, Emma, Chen, George, Kanjilal, Sanjat, Oberst, Michael, Zhang, Linying, Singh, Harvineet, Hartvigsen, Tom, Zhou, Helen, Okolo, Chinasa T.
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 participants and senior researchers on timely and relevant topics for
Externí odkaz:
http://arxiv.org/abs/2403.01628
Autor:
Han, William Jongwon, Gomez, Diana, Alok, Avi, Duan, Chaojing, Rosenberg, Michael A., Weber, Douglas, Liu, Emerson, Zhao, Ding
Understanding the irregular electrical activity of atrial fibrillation (AFib) has been a key challenge in electrocardiography. For serious cases of AFib, catheter ablations are performed to collect intracardiac electrograms (EGMs). EGMs offer intrica
Externí odkaz:
http://arxiv.org/abs/2402.01115
Large Language models (LLMs) have shown remarkable success in assisting robot learning tasks, i.e., complex household planning. However, the performance of pretrained LLMs heavily relies on domain-specific templated text data, which may be infeasible
Externí odkaz:
http://arxiv.org/abs/2306.05696
Autor:
Qiu, Jielin, Zhu, Jiacheng, Han, William, Kumar, Aditesh, Mittal, Karthik, Jin, Claire, Yang, Zhengyuan, Li, Linjie, Wang, Jianfeng, Zhao, Ding, Li, Bo, Wang, Lijuan
Multimodal summarization with multimodal output (MSMO) has emerged as a promising research direction. Nonetheless, numerous limitations exist within existing public MSMO datasets, including insufficient maintenance, data inaccessibility, limited size
Externí odkaz:
http://arxiv.org/abs/2306.04216
Autor:
Qiu, Jielin, Zhu, Jiacheng, Liu, Shiqi, Han, William, Zhang, Jingqi, Duan, Chaojing, Rosenberg, Michael, Liu, Emerson, Weber, Douglas, Zhao, Ding
Automated interpretation of electrocardiograms (ECG) has garnered significant attention with the advancements in machine learning methodologies. Despite the growing interest, most current studies focus solely on classification or regression tasks, wh
Externí odkaz:
http://arxiv.org/abs/2304.06286
Autor:
Qiu, Jielin, Han, William, Zhu, Jiacheng, Xu, Mengdi, Rosenberg, Michael, Liu, Emerson, Weber, Douglas, Zhao, Ding
Recent advancements in Large Language Models (LLMs) have drawn increasing attention since the learned embeddings pretrained on large-scale datasets have shown powerful ability in various downstream applications. However, whether the learned knowledge
Externí odkaz:
http://arxiv.org/abs/2301.09017
Brain Signals, such as Electroencephalography (EEG), and human languages have been widely explored independently for many downstream tasks, however, the connection between them has not been well explored. In this study, we explore the relationship an
Externí odkaz:
http://arxiv.org/abs/2208.06348
Autor:
Qiu, Jielin, Zhu, Jiacheng, Liu, Shiqi, Han, William, Zhang, Jingqi, Duan, Chaojing, Rosenberg, Michael, Liu, Emerson, Weber, Douglas, Zhao, Ding
Automated interpretation of electrocardiograms (ECG) has garnered significant attention with the advancements in machine learning methodologies. Despite the growing interest in automated ECG interpretation using machine learning, most current studies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ed565b4bbf06833618c74d89a90c990