3 citations · 5 across the 4 of their papers we have counts for
4 papers
printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning
Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan +1
Nowadays, modern recommender systems usually leverage textual and visual contents as auxiliary information to predict user preference. For textual information, review texts are one…
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation
Xiusi Chen, Yu Zhang, Jinliang Deng +2
Few-shot question answering (QA) aims at precisely discovering answers to a set of questions from context passages while only a few training samples are available. Although existin…
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation
Eli Chien, Jiong Zhang, Cho-Jui Hsieh +4
The eXtreme Multi-label Classification~(XMC) problem seeks to find relevant labels from an exceptionally large label space. Most of the existing XMC learners focus on the extractio…
InfluencerRank: Discovering Effective Influencers via Graph Convolutional Attentive Recurrent Neural Networks
Seungbae Kim, Jyun-Yu Jiang, Jinyoung Han +1
As influencers play considerable roles in social media marketing, companies increase the budget for influencer marketing. Hiring effective influencers is crucial in social influenc…