Search Results for author: Xinyan Zhao

Found 13 papers, 3 papers with code

Identifying Medication Abuse and Adverse Effects from Tweets: University of Michigan at #SMM4H 2020

no code implementations SMM4H (COLING) 2020 V.G.Vinod Vydiswaran, Deahan Yu, Xinyan Zhao, Ermioni Carr, Jonathan Martindale, Jingcheng Xiao, Noha Ghannam, Matteo Althoen, Alexis Castellanos, Neel Patel, Daniel Vasquez

The team from the University of Michigan participated in three tasks in the Social Media Mining for Health Applications (#SMM4H) 2020 shared tasks – on detecting mentions of adverse effects (Task 2), extracting and normalizing them (Task 3), and detecting mentions of medication abuse (Task 4).

Task 2

Narrative Detection and Feature Analysis in Online Health Communities

no code implementations NAACL (WNU) 2022 Achyutarama Ganti, Steven Wilson, Zexin Ma, Xinyan Zhao, Rong Ma

Narratives have been shown to be an effective way to communicate health risks and promote health behavior change, and given the growing amount of health information being shared on social media, it is crucial to study health-related narratives in social media.

text-classification Text Classification

Tailoring Generative AI Chatbots for Multiethnic Communities in Disaster Preparedness Communication: Extending the CASA Paradigm

no code implementations12 Jun 2024 Xinyan Zhao, Yuan Sun, Wenlin Liu, Chau-Wai Wong

This study is among the first to develop different prototypes of generative AI (GenAI) chatbots powered by GPT 4 to communicate hurricane preparedness information to diverse residents.

Chatbot

Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users

1 code implementation31 Oct 2023 Yohan Jo, Xinyan Zhao, Arijit Biswas, Nikoletta Basiou, Vincent Auvray, Nikolaos Malandrakis, Angeliki Metallinou, Alexandros Potamianos

While most task-oriented dialogues assume conversations between the agent and one user at a time, dialogue systems are increasingly expected to communicate with multiple users simultaneously who make decisions collaboratively.

Decision Making Dialogue State Tracking

PharmMT: A Neural Machine Translation Approach to Simplify Prescription Directions

no code implementations Findings of the Association for Computational Linguistics 2020 Jiazhao Li, Corey Lester, Xinyan Zhao, Yuting Ding, Yun Jiang, V. G. Vinod Vydiswaran

We propose a novel machine translation-based approach, PharmMT, to automatically and reliably simplify prescription directions into patient-friendly language, thereby significantly reducing pharmacist workload.

Machine Translation Translation

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

1 code implementation EACL 2021 Xinyan Zhao, Haibo Ding, Zhe Feng

Instead of using expensive manual annotations, researchers have proposed to train named entity recognition (NER) systems using heuristic labeling rules.

Graph Neural Network named-entity-recognition +3

Toward Effective Automated Content Analysis via Crowdsourcing

no code implementations12 Jan 2021 Jiele Wu, Chau-Wai Wong, Xinyan Zhao, Xianpeng Liu

For subjective features such as semantic connotation, online workers, known for optimizing their hourly earnings, tend to deteriorate in the quality of their responses as they work longer.

LIREx: Augmenting Language Inference with Relevant Explanation

1 code implementation16 Dec 2020 Xinyan Zhao, V. G. Vinod Vydiswaran

Natural language explanations (NLEs) are a special form of data annotation in which annotators identify rationales (most significant text tokens) when assigning labels to data instances, and write out explanations for the labels in natural language based on the rationales.

Explanation Generation Natural Language Inference

A Weighted Heterogeneous Graph Based Dialogue System

no code implementations21 Oct 2020 Xinyan Zhao, LiangWei Chen, Huanhuan Chen

Most research on disease diagnosis dialogue systems highly rely on data-driven methods and statistical features, lacking profound comprehension of symptom-disease relations and symptom-symptom relations.

Attribute Dialogue Management +1

Correction of Faulty Background Knowledge based on Condition Aware and Revise Transformer for Question Answering

no code implementations30 Jun 2020 Xinyan Zhao, Xiao Feng, Haoming Zhong, Jun Yao, Huanhuan Chen

CAR-Transformer (1) revises each condition value based on the whole conversation and original conditions values, and (2) it encodes the revised conditions and utilizes the conditions embedding to select an answer.

Question Answering

Theme-aware generation model for chinese lyrics

no code implementations23 May 2019 Jie Wang, Xinyan Zhao

With rapid development of neural networks, deep-learning has been extended to various natural language generation fields, such as machine translation, dialogue generation and even literature creation.

Dialogue Generation Machine Translation +1

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