Congrat: Self-supervised contrastive pretraining for joint graph and text embeddings
Learning on text-attributed graphs (TAGs), in which nodes are associated with one or more
texts, has been the subject of much recent work. However, most approaches tend to make …
texts, has been the subject of much recent work. However, most approaches tend to make …
Tweetnerd-end to end entity linking benchmark for tweets
Abstract Named Entity Recognition and Disambiguation (NERD) systems are foundational
for information retrieval, question answering, event detection, and other natural language …
for information retrieval, question answering, event detection, and other natural language …
MM-EMOR: Multi-Modal Emotion Recognition of Social Media Using Concatenated Deep Learning Networks
O Adel, KM Fathalla, A Abo ElFarag - Big Data and Cognitive Computing, 2023 - mdpi.com
Emotion recognition is crucial in artificial intelligence, particularly in the domain of human–
computer interaction. The ability to accurately discern and interpret emotions plays a critical …
computer interaction. The ability to accurately discern and interpret emotions plays a critical …
Large Language Model-Guided Disentangled Belief Representation Learning on Polarized Social Graphs
The paper advances belief representation learning in polarized networks–the mapping of
social beliefs espoused by users and posts in a polarized network into a disentangled latent …
social beliefs espoused by users and posts in a polarized network into a disentangled latent …
Hierarchical regression model tree for explainable actor segmentation and response prediction on social networks
J Li - 2022 - ideals.illinois.edu
Social network systems have produced large-scale data of social signals. However, the
potential mechanism of social signal propagation and how it affects people's beliefs and …
potential mechanism of social signal propagation and how it affects people's beliefs and …