12 citations · 18 across the 8 of their papers we have counts for
8 papers
Querying Climate Knowledge: Semantic Retrieval for Scientific Discovery
Mustapha Adamu, Qi Zhang, Huitong Pan +2
The growing complexity and volume of climate science literature make it increasingly difficult for researchers to find relevant information across models, datasets, regions, and va…
DynClean: Training Dynamics-based Label Cleaning for Distantly-Supervised Named Entity Recognition
Qi Zhang, Huitong Pan, Zhijia Chen +3
Distantly Supervised Named Entity Recognition (DS-NER) has attracted attention due to its scalability and ability to automatically generate labeled data. However, distant annotatio…
SciER: An Entity and Relation Extraction Dataset for Datasets, Methods, and Tasks in Scientific Documents
Qi Zhang, Zhijia Chen, Huitong Pan +3
Scientific information extraction (SciIE) is critical for converting unstructured knowledge from scholarly articles into structured data (entities and relations). Several datasets…
FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding
Huitong Pan, Qi Zhang, Cornelia Caragea +2
Flowcharts are graphical tools for representing complex concepts in concise visual representations. This paper introduces the FlowLearn dataset, a resource tailored to enhance the…
SciDMT: A Large-Scale Corpus for Detecting Scientific Mentions
Huitong Pan, Qi Zhang, Cornelia Caragea +2
We present SciDMT, an enhanced and expanded corpus for scientific mention detection, offering a significant advancement over existing related resources. SciDMT contains annotated s…
DMDD: A Large-Scale Dataset for Dataset Mentions Detection
Huitong Pan, Qi Zhang, Eduard Dragut +2
The recognition of dataset names is a critical task for automatic information extraction in scientific literature, enabling researchers to understand and identify research opportun…
Prostate Segmentation from 3D MRI Using a Two-Stage Model and Variable-Input Based Uncertainty Measure
Huitong Pan, Yushan Feng, Quan Chen +2
This paper proposes a two-stage segmentation model, variable-input based uncertainty measures and an uncertainty-guided post-processing method for prostate segmentation on 3D magne…
A Self-Adaptive Network For Multiple Sclerosis Lesion Segmentation From Multi-Contrast MRI With Various Imaging Protocols
Yushan Feng, Huitong Pan, Craig Meyer +1
Deep neural networks (DNN) have shown promises in the lesion segmentation of multiple sclerosis (MS) from multicontrast MRI including T1, T2, proton density (PD) and FLAIR sequence…