134 citations · 137 across the 5 of their papers we have counts for
5 papers
Improving Representation Learning for Histopathologic Images with Cluster Constraints
Weiyi Wu, Chongyang Gao, Joseph DiPalma +2
Recent advances in whole-slide image (WSI) scanners and computational capabilities have significantly propelled the application of artificial intelligence in histopathology slide a…
Proto-lm: A Prototypical Network-Based Framework for Built-in Interpretability in Large Language Models
Sean Xie, Soroush Vosoughi, Saeed Hassanpour
Large Language Models (LLMs) have significantly advanced the field of Natural Language Processing (NLP), but their lack of interpretability has been a major concern. Current method…
Graph-Level Embedding for Time-Evolving Graphs
Lili Wang, Chenghan Huang, Weicheng Ma +2
Graph representation learning (also known as network embedding) has been extensively researched with varying levels of granularity, ranging from nodes to graphs. While most prior w…
Capturing Topic Framing via Masked Language Modeling
Xiaobo Guo, Weicheng Ma, Soroush Vosoughi
Differential framing of issues can lead to divergent world views on important issues. This is especially true in domains where the information presented can reach a large audience,…
Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder
Soroush Vosoughi, Prashanth Vijayaraghavan, Deb Roy
We present Tweet2Vec, a novel method for generating general-purpose vector representation of tweets. The model learns tweet embeddings using character-level CNN-LSTM encoder-decode…