1 code implementation • 25 Sep 2024 • Yan-Ying Chen, Shabnam Hakimi, Monica Van, Francine Chen, Matthew Hong, Matt Klenk, Charlene Wu
Product images (e. g., a phone) can be used to elicit a diverse set of consumer-reported features expressed through language, including surface-level perceptual attributes (e. g., "white") and more complex ones, like perceived utility (e. g., "battery").
no code implementations • 9 Feb 2022 • Nikos Arechiga, Francine Chen, Rumen Iliev, Emily Sumner, Scott Carter, Alex Filipowicz, Nayeli Bravo, Monica Van, Kate Glazko, Kalani Murakami, Laurent Denoue, Candice Hogan, Katharine Sieck, Charlene Wu, Kent Lyons
In this work, we focus on methods for personalizing interventions based on an individual's demographics to shift the preferences of consumers to be more positive towards Battery Electric Vehicles (BEVs).
no code implementations • 7 Dec 2021 • Nikos Arechiga, Francine Chen, Yan-Ying Chen, Yanxia Zhang, Rumen Iliev, Heishiro Toyoda, Kent Lyons
We develop a deep neural network (MACSYMA) to address the symbolic regression problem as an end-to-end supervised learning problem.
no code implementations • EACL (AdaptNLP) 2021 • Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schuetze
Interleaved texts, where posts belonging to different threads occur in a sequence, commonly occur in online chat posts, so that it can be time-consuming to quickly obtain an overview of the discussions.
no code implementations • 1 Aug 2020 • Takanori Fujiwara, Jian Zhao, Francine Chen, Kwan-Liu Ma
A common network analysis task is comparison of two networks to identify unique characteristics in one network with respect to the other.
no code implementations • 7 Jun 2020 • Cheng Zhang, Francine Chen, Yan-Ying Chen
In this paper, we propose an alternative approach that learns discriminative features among triplets of images and cyclically trains on region features to verify whether attentive regions contain information indicative of a disease.
3 code implementations • 25 May 2020 • Takanori Fujiwara, Jian Zhao, Francine Chen, Yao-Liang Yu, Kwan-Liu Ma
This analysis task could be greatly assisted by contrastive learning, which is an emerging analysis approach to discover salient patterns in one dataset relative to another.
no code implementations • 25 Sep 2019 • Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schütze
The interleaved posts are encoded hierarchically, i. e., word-to-word (words in a post) followed by post-to-post (posts in a channel).
no code implementations • 6 Aug 2019 • Philipp Harzig, Yan-Ying Chen, Francine Chen, Rainer Lienhart
Automatic medical report generation from chest X-ray images is one possibility for assisting doctors to reduce their workload.
no code implementations • ACL 2019 • Francine Chen, Yan-Ying Chen
A common issue in training a deep learning, abstractive summarization model is lack of a large set of training summaries.
no code implementations • 5 Jun 2019 • Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schütze
Interleaved texts, where posts belonging to different threads occur in one sequence, are a common occurrence, e. g., online chat conversations.
no code implementations • EMNLP 2018 • Ryuji Kano, Yasuhide Miura, Motoki Taniguchi, Yan-Ying Chen, Francine Chen, Tomoko Ohkuma
We leverage a popularity measure in social media as a distant label for extractive summarization of online conversations.
no code implementations • NAACL 2018 • Jyun-Yu Jiang, Francine Chen, Yan-Ying Chen, Wei Wang
An enormous amount of conversation occurs online every day, such as on chat platforms where multiple conversations may take place concurrently.
no code implementations • EACL 2017 • Heike Adel, Francine Chen, Yan-Ying Chen
Users often use social media to share their interest in products.
no code implementations • LREC 2016 • Shigeyuki Sakaki, Francine Chen, M Korpusik, y, Yan-Ying Chen
These posts may include information about the purchase activity of people, and insights useful to companies can be derived from them: e. g. profile information of a user who mentioned something about their product.