Summary of Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networks, By Jaehyun Lee et al.
Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networksby Jaehyun Lee, SeongKu Kang,…
Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networksby Jaehyun Lee, SeongKu Kang,…
Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendationby Nicholas Sukiennik, Chen Gao, Nian…
Towards Automatic Composition of ASP Programs from Natural Language Specificationsby Manuel Borroto, Irfan Kareem, Francesco…
Personalizing explanations of AI-driven hints to users’ cognitive abilities: an empirical evaluationby Vedant Bahel, Harshinee…
Guiding Enumerative Program Synthesis with Large Language Modelsby Yixuan Li, Julian Parsert, Elizabeth PolgreenFirst submitted…
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Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selectionby Jianfeng He, Hang Su, Jason Cai, Igor…
Natural Language Processing in Patents: A Surveyby Lekang Jiang, Stephan GoetzFirst submitted to arxiv on:…
The Cognitive Type Project – Mapping Typography to Cognitionby Nik Bear BrownFirst submitted to arxiv…
Understanding Biology in the Age of Artificial Intelligenceby Elsa Lawrence, Adham El-Shazly, Srijit Seal, Chaitanya…