Zero Shot Learning in Scene Graph Generation
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Updated
Aug 12, 2020 - Python
Zero Shot Learning in Scene Graph Generation
ZSRGAN: Zero-shot Super-Resolution with Generative Adversarial Network(Pytorch)
This is a project I had done over my 10-week internship at ORNL. The goal of this project was to use different Computer Vision Techniques to classify pictures of blurred car cabin images
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Improving Zero-Shot Cross-Lingual Hate Speech Detection with Pseudo-Label Fine-Tuning of Transformer Language Models
Convergence [Python application] [Python training] [Python technology sharing] and so on
Task Generation Scheme for the Meta-Unsupervised Algorithm
LLMs for Low Resource Languages in Multilingual, Multimodal and Dialectal Settings
My Master Thesis on Zero-shot Multilingual Relation Extraction as Question Answering
Zero-shot LM prompting framework that uses procedural reasoning to solve complex knowledge graph based questions
Forecasting the air quality of regions in Delhi using LLMs
The official repository of the "Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning" paper published at ICLR 2022.
Sentiment analysis on Amazon Fine Food Dataset available on Kaggle Using Zero-Shot Learning
Zero-shot learning (ZSL) is a challenging problem in computer vision, where the model is required to recognize classes that have not been seen during training.
Demonstration of LLM techniques such as prompt engineering, full finetuning, PEFT (LoRA) etc.
Reproducibility Challenge for COMP6248 Deep Learning module (University of Southampton)
zero-shot super resolution
Code and pre-processed data for our paper in AAAI 2022 named CABACE.
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