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Found 10 papers, 2 papers with code
Accuracy meets Diversity in a News Recommender System
We customize an augmented vector for each query and news item to introduce information interaction between the two towers.
Incorporating Medical Knowledge to Transformer-based Language Models for Medical Dialogue Generation
In this study, we propose a new method that addresses the challenges of medical dialogue generation by incorporating medical knowledge into transformer-based language models.
NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media
To bridge this gap, we posit two significant dimensions: (1) Causal analysis to illustrate a cause and effect relationship in the user generated text; (2) Perception mining to infer psychological perspectives of social effects on online users intentions.
An Approach to Ensure Fairness in News Articles
This paper introduces Dbias, which is a Python package to ensure fairness in news articles.
Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model
We present and release PHS-BERT, a transformer-based PLM, to identify tasks related to public health surveillance on social media.
Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
We present BioALBERT, a domain-specific adaptation of A Lite Bidirectional Encoder Representations from Transformers (ALBERT), trained on biomedical (PubMed and PubMed Central) and clinical (MIMIC-III) corpora and fine tuned for 6 different tasks across 20 benchmark datasets.
Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU
In this study, to classify vaccine sentiment tweets with limited information, we present a novel end-to-end framework consisting of interconnected components that use domain-specific LM trained on vaccine-related tweets and models commonsense knowledge into a bidirectional gated recurrent network (CK-BiGRU) with context-aware attention.
Text Mining of Stocktwits Data for Predicting Stock Prices
These datasets were labelled with three labelling techniques based on stock price changes.
A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models
In this survey, we explore different word representation models and its power of expression, from the classical to modern-day state-of-the-art word representation language models (LMS).
BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition
In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recognition (BioNER) has increased exponentially.
