1 code implementation • LREC (LAW) 2022 • Nicholas Elder, Robert E. Mercer, Sudipta Singha Roy
This paper presents a method for semi-automatically building a corpus of full-text English-language biomedical articles annotated with part-of-speech tags.
no code implementations • BioNLP (ACL) 2022 • Sudipta Singha Roy, Robert E. Mercer
This paper suggests a mechanism for linking citing sentences in a publication with cited sentences in referenced sources.
no code implementations • COLING 2022 • Waqar Bin Kalim, Robert E. Mercer
Using this silver standard corpus we train two machine learning algorithms to automatically extract method entities from biomedical text.
1 code implementation • LREC 2022 • 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.
no code implementations • COLING (ArgMining) 2020 • Eli Moser, Robert E. Mercer
The tendency for claims to use other claims as their supporting evidence in addition to the experimental data led to two novel models that have provided a better understanding of the large scale argumentation structure of a complete biochemistry paper.
1 code implementation • ArgMining (ACL) 2022 • Muhammad Tawsif Sazid, Robert E. Mercer
We develop a novel unified representation for the argumentation mining task facilitating the extracting from text and the labelling of the non-argumentative units and argumentation components—premises, claims, and major claims—and the argumentative relations—premise to claim or premise in a support or attack relation, and claim to major-claim in a for or against relation—in an end-to-end machine learning pipeline.
no code implementations • LREC 2022 • Sudipta Singha Roy, Robert E. Mercer
In this paper, to find these citation linkages in biomedical research publications using deep learning, we provide a synthetic silver standard corpus as well as the method to build this corpus.
1 code implementation • 28 Jul 2023 • Xindi Wang, YuFei Wang, Can Xu, Xiubo Geng, BoWen Zhang, Chongyang Tao, Frank Rudzicz, Robert E. Mercer, Daxin Jiang
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 explicitly pre-trained.
no code implementations • 28 Apr 2022 • 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.
1 code implementation • LREC 2022 • Vladimir Araujo, Andrés Carvallo, Souvik Kundu, José Cañete, Marcelo Mendoza, Robert E. Mercer, Felipe Bravo-Marquez, Marie-Francine Moens, Alvaro Soto
Due to the success of pre-trained language models, versions of languages other than English have been released in recent years.
1 code implementation • ACL 2022 • 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 relevant information.
no code implementations • LREC 2020 • Mahtab Ahmed, Chahna Dixit, Robert E. Mercer, Atif Khan, Muhammad Rifayat Samee, Felipe Urra
In this work, we describe a semi-automated framework to create a multilingual corpus which can be used for the multilingual semantic similarity task.
no code implementations • LREC 2020 • Jumayel Islam, Lu Xiao, Robert E. Mercer
Our work produced three manually constructed lists of hedge words, booster words, and hedging phrases.
no code implementations • WS 2019 • Mohammed Alliheedi, Robert E. Mercer, Robin Cohen
In particular, we conduct a detailed study with human annotators to confirm that our selection of semantic roles is effective in determining the underlying rhetorical structure of existing biomedical articles in an extensive dataset.
1 code implementation • WS 2019 • Xindi Wang, Robert E. Mercer
The goal of text classification is to automatically assign categories to documents.
no code implementations • ACL 2019 • Mahtab Ahmed, Muhammad Rifayat Samee, Robert E. Mercer
To this end, we propose Tree Transformer, a model that captures phrase level syntax for constituency trees as well as word-level dependencies for dependency trees by doing recursive traversal only with attention.
no code implementations • NAACL 2019 • Jumayel Islam, Robert E. Mercer, Lu Xiao
It provides a great way to understand human psychology and impose a challenge to researchers to analyze their content easily.
no code implementations • 1 Jan 2019 • Mahtab Ahmed, Muhammad Rifayat Samee, Robert E. Mercer
In Natural Language Processing (NLP), we often need to extract information from tree topology.
no code implementations • 4 Sep 2018 • Mahtab Ahmed, Muhammad Rifayat Samee, Robert E. Mercer
Word sense disambiguation (WSD) is a well researched problem in computational linguistics.
no code implementations • 27 Jul 2018 • Mahtab Ahmed, Muhammad Rifayat Samee, Robert E. Mercer
Sequence labelling is the task of assigning categorical labels to a data sequence.
no code implementations • 30 Jul 2013 • Rushdi Shams, Robert E. Mercer
We rank sentences of a text according to their FI and select 30 percent of the most difficult sentences.