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Found 19 papers, 5 papers with code
Examining the Causal Effect of First Names on Language Models: The Case of Social Commonsense Reasoning
As language models continue to be integrated into applications of personal and societal relevance, ensuring these models' trustworthiness is crucial, particularly with respect to producing consistent outputs regardless of sensitive attributes.
Complementary and Integrative Health Lexicon (CIHLex) and Entity Recognition in the Literature
Results: From the 198 unique concepts in CIHLex, 62. 1% could be matched to at least one term in the UMLS.
Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation
Improving the emotional awareness of pre-trained language models is an emerging important problem for dialogue generation tasks.
Developing a Knowledge Graph Framework for Pharmacokinetic Natural Product-Drug Interactions
NP-KG is a heterogeneous KG with biomedical ontologies, linked data, and full texts of the scientific literature, constructed with the Phenotype Knowledge Translator framework and the semantic relation extraction systems, SemRep and Integrated Network and Dynamic Reasoning Assembler.
UIUC\_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions
We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP publications.
Discovering novel drug-supplement interactions using a dietary supplements knowledge graph generated from the biomedical literature
MATERIALS AND METHODS: We created SemRepDS (an extension of SemRep), capable of extracting semantic relations from abstracts by leveraging a DS-specific terminology (iDISK) containing 28, 884 DS terms not found in the UMLS.
UIUC_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions
We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP publications.
Drug Repurposing for COVID-19 via Knowledge Graph Completion
The models were trained and assessed using a time slicing approach and the predicted drugs were compared with a list of drugs reported in the literature and evaluated in clinical trials.
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels
As drug-drug interactions (DDIs) may lead to preventable adverse events, being able to extract DDIs from drug labels into a machine-processable form is an important step toward effective dissemination of drug safety information.
A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels
As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels into machine-readable form is an important effort in effectively deploying drug safety information.
TextFlow: A Text Similarity Measure based on Continuous Sequences
Text similarity measures are used in multiple tasks such as plagiarism detection, information ranking and recognition of paraphrases and textual entailment.
Annotating Named Entities in Consumer Health Questions
We describe a corpus of consumer health questions annotated with named entities.
Annotating Question Decomposition on Complex Medical Questions
This paper presents a method for annotating question decomposition on complex medical questions.
