Final Project of Applied Deep Learning (ADL Lectured by Yun-Nung Chen at NTU)
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Updated
Jan 18, 2022 - Python
Final Project of Applied Deep Learning (ADL Lectured by Yun-Nung Chen at NTU)
Weak Supervised Fake News Detection with RoBERTa, XLNet, ALBERT, XGBoost and Logistic Regression classifiers.
Mitigating a language model's over-confidence with NLI predictions on Multi-NLI hypotheses with random word order using PAWS (paraphrase) and Winogrande (anaphora).
Large Language Model | BERT (Bidirectional Encoder Representations from Transformers)
Multi Label Text Classification of ICD-10-CM codes on the clinical record corpus for eHealth Lab CLEF - 2020
Extracting Emotion-Cause Pairs from Conversations: A Two-Step Approach Using Emotion Classification and QA Models
Fine-tuning BERT model on a limited dataset featuring customer feedback for British Airways.
Welcome to our RoBERTa Sentiment Analysis project! In this repository, we explore the world of Natural Language Processing (NLP) by fine-tuning a RoBERTa Transformer for sentiment analysis.
Chinese Offensive Language Detection using onnx model
A comparative study for fake news detection using deep learning techniques.
Time perception analysis for borderline personality disorder patients
This repository contains the annotated dataset, the unigrams, bigrams and trigrams referenced in the paper "COVID-19 Vaccine Hesitancy in the Month Following the Start of the Vaccination Process" published in the International Journal of Environmental Research and Public Health.
This repository contains all the programming assignments for the Applied Natural Language Processing class at the University of Southern California in the Spring 2022 semester.
Visual Question Answering Pipeline using Image Captioning and Wikipedia
An API for detecting hate speech related to Philippine elections and politics.
A PyTorch Library for Sequence Labeling Tasks such as Named-entity Recognition or Part-of-speech Tagging
The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMA
Comparative analysis of Bert Variants on MELD, Go_Emotions benchmark datasets.
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