no code implementations • 8 May 2024 • Juan He, Xiaoyan Wang, Long Chen, Yunpeng Cai, Zhengshan Wang
To address this issue, we propose an innovative approach based on deep learning to predict the progression of wound healing by analyzing collagen fiber features in histological images of wound tissue.
1 code implementation • 6 Jan 2024 • Zeju Li, Chao Zhang, Xiaoyan Wang, Ruilong Ren, Yifan Xu, Ruifei Ma, Xiangde Liu
The remarkable potential of multi-modal large language models (MLLMs) in comprehending both vision and language information has been widely acknowledged.
no code implementations • 20 Dec 2023 • Bichen Wu, Ching-Yao Chuang, Xiaoyan Wang, Yichen Jia, Kapil Krishnakumar, Tong Xiao, Feng Liang, Licheng Yu, Peter Vajda
In this paper, we introduce Fairy, a minimalist yet robust adaptation of image-editing diffusion models, enhancing them for video editing applications.
1 code implementation • 6 Dec 2023 • Zhixing Zhang, Bichen Wu, Xiaoyan Wang, Yaqiao Luo, Luxin Zhang, Yinan Zhao, Peter Vajda, Dimitris Metaxas, Licheng Yu
Given a video, a masked region at its initial frame, and an editing prompt, it requires a model to do infilling at each frame following the editing guidance while keeping the out-of-mask region intact.
no code implementations • 14 Feb 2021 • Xiaoyan Wang, Xi Lin, Meng Li
We call such a mobility market with AV renting options the "AV crowdsourcing market".
no code implementations • 20 Dec 2020 • Matthew T. Dearing, Xiaoyan Wang
Many interesting datasets ubiquitous in machine learning and deep learning can be described via graphs.
1 code implementation • 17 Oct 2020 • Sourabh Kulkarni, Kinjal Divesh Shah, Nimar Arora, Xiaoyan Wang, Yucen Lily Li, Nazanin Khosravani Tehrani, Michael Tingley, David Noursi, Narjes Torabi, Sepehr Akhavan Masouleh, Eric Lippert, Erik Meijer
The benchmark includes data generation and evaluation code for a number of models as well as implementations in some common PPLs.
1 code implementation • ACL 2020 • Nuo Xu, Pinghui Wang, Long Chen, Li Pan, Xiaoyan Wang, Junzhou Zhao
Legal Judgment Prediction (LJP) is the task of automatically predicting a law case's judgment results given a text describing its facts, which has excellent prospects in judicial assistance systems and convenient services for the public.
no code implementations • 11 Nov 2019 • Yunan Zhang, Xiang Cheng, Yufeng Zhang, Zihan Wang, Zhengqi Fang, Xiaoyan Wang, Zhenya Huang, ChengXiang Zhai
Answering complex questions involving multiple entities and relations is a challenging task.
no code implementations • 24 Aug 2019 • Xiaoyan Wang, Ran Li, Bowei Yan, Oluwasanmi Koyejo
We propose a framework for constructing and analyzing multiclass and multioutput classification metrics, i. e., involving multiple, possibly correlated multiclass labels.
no code implementations • AKBC 2019 • Ryan Musa, Xiaoyan Wang, Achille Fokoue, Nicholas Mattei, Maria Chang, Pavan Kapanipathi, Bassem Makni, Kartik Talamadupula, Michael Witbrock
Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques.
no code implementations • 15 Sep 2018 • Ryan Musa, Xiaoyan Wang, Achille Fokoue, Nicholas Mattei, Maria Chang, Pavan Kapanipathi, Bassem Makni, Kartik Talamadupula, Michael Witbrock
Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques.
no code implementations • 15 Sep 2018 • Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa, Mo Yu, Kartik Talamadupula, Ibrahim Abdelaziz, Maria Chang, Achille Fokoue, Bassem Makni, Nicholas Mattei, Michael Witbrock
To address this, we present a combination of techniques that harness knowledge graphs to improve performance on the NLI problem in the science questions domain.