29 citations · 34 across the 9 of their papers we have counts for
11 papers
A Domain-Adapted Pipeline for Structured Information Extraction from Police Incident Announcements on Social Media
Mengfan Shen, Kangqi Song, Xindi Wang +3
Structured information extraction from police incident announcements is crucial for timely and accurate data processing, yet presents considerable challenges due to the variability…
Trustworthy Medical Question Answering: An Evaluation-Centric Survey
Yinuo Wang, Baiyang Wang, Robert E. Mercer +5
Trustworthiness in healthcare question-answering (QA) systems is important for ensuring patient safety, clinical effectiveness, and user confidence. As large language models (LLMs)…
Graph-tree Fusion Model with Bidirectional Information Propagation for Long Document Classification
Sudipta Singha Roy, Xindi Wang, Robert E. Mercer +1
Long document classification presents challenges in capturing both local and global dependencies due to their extensive content and complex structure. Existing methods often strugg…
Multi-stage Retrieve and Re-rank Model for Automatic Medical Coding Recommendation
Xindi Wang, Robert E. Mercer, Frank Rudzicz
The International Classification of Diseases (ICD) serves as a definitive medical classification system encompassing a wide range of diseases and conditions. The primary objective…
Auxiliary Knowledge-Induced Learning for Automatic Multi-Label Medical Document Classification
Xindi Wang, Robert E. Mercer, Frank Rudzicz
The International Classification of Diseases (ICD) is an authoritative medical classification system of different diseases and conditions for clinical and management purposes. ICD…
Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models
Xindi Wang, Mahsa Salmani, Parsa Omidi +3
Recently, large language models (LLMs) have shown remarkable capabilities including understanding context, engaging in logical reasoning, and generating responses. However, this is…
Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning
Xindi Wang, Yufei Wang, Can Xu +6
Large language models (LLMs) have shown remarkable capacity for in-context learning (ICL), where learning a new task from just a few training examples is done without being explici…
MeSHup: A Corpus for Full Text Biomedical Document Indexing
Xindi Wang, Robert E. Mercer, Frank Rudzicz
Medical Subject Heading (MeSH) indexing refers to the problem of assigning a given biomedical document with the most relevant labels from an extremely large set of MeSH terms. Curr…
KenMeSH: Knowledge-enhanced End-to-end Biomedical Text Labelling
Xindi Wang, Robert E. Mercer, Frank Rudzicz
Currently, Medical Subject Headings (MeSH) are manually assigned to every biomedical article published and subsequently recorded in the PubMed database to facilitate retrieving rel…
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
John Chen, Ian Berlot-Attwell, Safwan Hossain +2
Clinical machine learning is increasingly multimodal, collected in both structured tabular formats and unstructured forms such as freetext. We propose a novel task of exploring fai…
End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models
John Giorgi, Xindi Wang, Nicola Sahar +3
Named entity recognition (NER) and relation extraction (RE) are two important tasks in information extraction and retrieval (IE \& IR). Recent work has demonstrated that it is bene…