Search Results for author:
Found 7 papers, 2 papers with code
Eraser: Jailbreaking Defense in Large Language Models via Unlearning Harmful Knowledge
Jailbreaking attacks can enable Large Language Models (LLMs) to bypass the safeguard and generate harmful content.
On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction
Recent zero-shot classification methods converted the task to other NLP tasks (e. g., textual entailment) and used off-the-shelf models of these NLP tasks to directly perform inference on the test data without using a large amount of IE annotation data.
Learning with Silver Standard Data for Zero-shot Relation Extraction
In this paper, we propose to first detect a small amount of clean data from silver standard data and then use the selected clean data to finetune the pretrained model.
Temperature Effect on Interactions of Oil Droplet with Water-wetted Shale Kerogen at Reservoir Temperatures
Kerogen was modeled with a molecular fragment from a type II kerogen.
Materials Science Chemical Physics 82D03 J.2
Implications of the virus-encoded miRNA and host miRNA in the pathogenicity of SARS-CoV-2
The outbreak of COVID-19 caused by SARS-CoV-2 has rapidly spread worldwide and has caused over 1, 400, 000 infections and 80, 000 deaths.
Genomics Biomolecules
Predicting the Results of LTL Model Checking using Multiple Machine Learning Algorithms
In this paper, we study how to predict the results of LTL model checking using some machine learning algorithms.
Joint Learning for Pulmonary Nodule Segmentation, Attributes and Malignancy Prediction
Refer to the literature of lung nodule classification, many studies adopt Convolutional Neural Networks (CNN) to directly predict the malignancy of lung nodules with original thoracic Computed Tomography (CT) and nodule location.
