activity
20172025
most citedMitigating Uncertainty in Document Classification

5 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2025

RailEstate: An Interactive System for Metro Linked Property Trends

Chen-Wei Chang, Yu-Chieh Cheng, Yun-En Tsai +2

Access to metro systems plays a critical role in shaping urban housing markets by enhancing neighborhood accessibility and driving property demand. We present RailEstate, a novel w…

cs.CL2023

TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation

Shuo Lei, Xuchao Zhang, Jianfeng He +2

Meta-learning has emerged as a trending technique to tackle few-shot text classification and achieve state-of-the-art performance. However, the performance of existing approaches h…

cs.CV2020★ 3 cited

Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations

Shuo Lei, Xuchao Zhang, Jianfeng He +2

Despite the great progress made by deep neural networks in the semantic segmentation task, traditional neural-networkbased methods typically suffer from a shortage of large amounts…

cs.LG2019★ 5 cited

Mitigating Uncertainty in Document Classification

Xuchao Zhang, Fanglan Chen, Chang-Tien Lu +1

The uncertainty measurement of classifiers' predictions is especially important in applications such as medical diagnoses that need to ensure limited human resources can focus on t…

cs.CY2017★ 2 cited

SAFEBIKE: A Bike-sharing Route Recommender with Availability Prediction and Safe Routing

Weisheng Zhong, Fanglan Chen, Kaiqun Fu +1

This paper presents SAFEBIKE, a novel route recommendation system for bike-sharing service that utilizes station information to infer the number of available bikes in dock and reco…