41 citations · 102 across the 18 of their papers we have counts for
18 papers
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
Jie Yang, Soyeon Caren Han, Siqu Long +2
Extracting meaningful drug-related information chunks, such as adverse drug events (ADE), is crucial for preventing morbidity and saving many lives. Most ADEs are reported via an u…
Social network modeling and applications, a tutorial
Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…
Tri-level Joint Natural Language Understanding for Multi-turn Conversational Datasets
Henry Weld, Sijia Hu, Siqu Long +2
Natural language understanding typically maps single utterances to a dual level semantic frame, sentence level intent and slot labels at the word level. The best performing models…
Form-NLU: Dataset for the Form Natural Language Understanding
Yihao Ding, Siqu Long, Jiabin Huang +4
Compared to general document analysis tasks, form document structure understanding and retrieval are challenging. Form documents are typically made by two types of authors; A form…
Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction
Soyeon Caren Han, Siqu Long, Henry Weld +1
When a human communicates with a machine using natural language on the web and online, how can it understand the human's intention and semantic context of their talk? This is an im…
PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionals
Zhihao Zhang, Siwen Luo, Junyi Chen +4
We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the fu…
SUPER-Rec: SUrrounding Position-Enhanced Representation for Recommendation
Taejun Lim, Siqu Long, Josiah Poon +1
Collaborative filtering problems are commonly solved based on matrix completion techniques which recover the missing values of user-item interaction matrices. In a matrix, the rati…
Understanding Attention for Vision-and-Language Tasks
Feiqi Cao, Soyeon Caren Han, Siqu Long +2
Attention mechanism has been used as an important component across Vision-and-Language(VL) tasks in order to bridge the semantic gap between visual and textual features. While atte…
Doc-GCN: Heterogeneous Graph Convolutional Networks for Document Layout Analysis
Siwen Luo, Yihao Ding, Siqu Long +2
Recognizing the layout of unstructured digital documents is crucial when parsing the documents into the structured, machine-readable format for downstream applications. Recent stud…
A Quantitative and Qualitative Analysis of Suicide Ideation Detection using Deep Learning
Siqu Long, Rina Cabral, Josiah Poon +1
For preventing youth suicide, social media platforms have received much attention from researchers. A few researches apply machine learning, or deep learning-based text classificat…
Vision-and-Language Pretrained Models: A Survey
Siqu Long, Feiqi Cao, Soyeon Caren Han +1
Pretrained models have produced great success in both Computer Vision (CV) and Natural Language Processing (NLP). This progress leads to learning joint representations of vision an…
ME-GCN: Multi-dimensional Edge-Embedded Graph Convolutional Networks for Semi-supervised Text Classification
Kunze Wang, Soyeon Caren Han, Siqu Long +1
Compared to sequential learning models, graph-based neural networks exhibit excellent ability in capturing global information and have been used for semi-supervised learning tasks.…
Understanding Graph Convolutional Networks for Text Classification
Soyeon Caren Han, Zihan Yuan, Kunze Wang +2
Graph Convolutional Networks (GCN) have been effective at tasks that have rich relational structure and can preserve global structure information of a dataset in graph embeddings.…
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling
Soyeon Caren Han, Siqu Long, Huichun Li +2
Intent classification and slot filling are two critical tasks for natural language understanding. Traditionally the two tasks proceeded independently. However, more recently joint…
GLocal-K: Global and Local Kernels for Recommender Systems
Soyeon Caren Han, Taejun Lim, Siqu Long +2
Recommender systems typically operate on high-dimensional sparse user-item matrices. Matrix completion is a very challenging task to predict one's interest based on millions of oth…
CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection
Henry Weld, Guanghao Huang, Jean Lee +6
Traditional toxicity detection models have focused on the single utterance level without deeper understanding of context. We introduce CONDA, a new dataset for in-game toxic langua…
VICTR: Visual Information Captured Text Representation for Text-to-Image Multimodal Tasks
Soyeon Caren Han, Siqu Long, Siwen Luo +2
Text-to-image multimodal tasks, generating/retrieving an image from a given text description, are extremely challenging tasks since raw text descriptions cover quite limited inform…
Detect All Abuse! Toward Universal Abusive Language Detection Models
Kunze Wang, Dong Lu, Soyeon Caren Han +2
Online abusive language detection (ALD) has become a societal issue of increasing importance in recent years. Several previous works in online ALD focused on solving a single abusi…