Universal Model in Online Customer Service

no code implementations • 24 Feb 2024 • Shu-Ting Pi, Cheng-Ping Hsieh, Qun Liu, Yuying Zhu

Our novel approach involves using machine learning techniques to tag customer questions in transcripts and create a repository of questions and corresponding labels.

Information Retrieval Retrieval +1

Teacher-Student Learning on Complexity in Intelligent Routing

no code implementations • 24 Feb 2024 • Shu-Ting Pi, Michael Yang, Yuying Zhu, Qun Liu

Customer service is often the most time-consuming aspect for e-commerce websites, with each contact typically taking 10-15 minutes.

DenseLight: Efficient Control for Large-scale Traffic Signals with Dense Feedback

1 code implementation • 13 Jun 2023 • Junfan Lin, Yuying Zhu, Lingbo Liu, Yang Liu, Guanbin Li, Liang Lin

1) The travel time of a vehicle is delayed feedback on the effectiveness of TSC policy at each traffic intersection since it is obtained after the vehicle has left the road network.

Deep Reinforcement Learning Reinforcement Learning (RL) +1

Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation

1 code implementation • 2 Jul 2021 • Lingbo Liu, Yuying Zhu, Guanbin Li, Ziyi Wu, Lei Bai, Liang Lin

In this work, we proposed a novel neural network module termed Heterogeneous Information Aggregation Machine (HIAM), which fully exploits heterogeneous information of historical data (e. g., incomplete OD matrices, unfinished order vectors, and DO matrices) to jointly learn the evolutionary patterns of OD and DO ridership.

Time Series Analysis

MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences

1 code implementation • NAACL 2021 • Jianing Yang, Yongxin Wang, Ruitao Yi, Yuying Zhu, Azaan Rehman, Amir Zadeh, Soujanya Poria, Louis-Philippe Morency

Human communication is multimodal in nature; it is through multiple modalities such as language, voice, and facial expressions, that opinions and emotions are expressed.

Emotion Recognition Multimodal Sentiment Analysis

What Gives the Answer Away? Question Answering Bias Analysis on Video QA Datasets

no code implementations • 7 Jul 2020 • Jianing Yang, Yuying Zhu, Yongxin Wang, Ruitao Yi, Amir Zadeh, Louis-Philippe Morency

In this paper, we analyze QA biases in popular video question answering datasets and discover pretrained language models can answer 37-48% questions correctly without using any multimodal context information, far exceeding the 20% random guess baseline for 5-choose-1 multiple-choice questions.

Multiple-choice Question Answering +1

CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition

1 code implementation • NAACL 2019 • Yuying Zhu, Guoxin Wang, Börje F. Karlsson

Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters.

Chinese Named Entity Recognition named-entity-recognition +4