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Found 5 papers, 0 papers with code
IIITN NLP at SMM4H 2021 Tasks: Transformer Models for Classification on Health-Related Imbalanced Twitter Datasets
With increasing users sharing health-related information on social media, there has been a rise in using social media for health monitoring and surveillance.
UPennHLP at WNUT-2020 Task 2 : Transformer models for classification of COVID19 posts on Twitter
Increasing usage of social media presents new non-traditional avenues for monitoring disease outbreaks, virus transmissions and disease progressions through user posts describing test results or disease symptoms.
SoftQE: Learned Representations of Queries Expanded by LLMs
We investigate the integration of Large Language Models (LLMs) into query encoders to improve dense retrieval without increasing latency and cost, by circumventing the dependency on LLMs at inference time.
Accelerating Gradient-based Meta Learner
Meta Learning has been in focus in recent years due to the meta-learner model's ability to adapt well and generalize to new tasks, thus, reducing both the time and data requirements for learning.
CBIR using Pre-Trained Neural Networks
Instead of the using a single model, we use a pretrained Inception V3 model, and extract activation of its last fully connected layer, which forms a low dimensional representation of the image.
