Amit Sheth

Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning

2019 · arXiv (Cornell University)

Learning the underlying patterns in data goes beyond instance-based generalization to external knowledge represented in structured graphs or networks. Deep learning that primarily constitutes neural computing stream in AI has shown significant advances in probabilistically …

KI-BERT: Infusing Knowledge Context for Better Language and Domain Understanding

2021 · arXiv (Cornell University)

Contextualized entity representations learned by state-of-the-art transformer-based language models (TLMs) like BERT, GPT, T5, etc., leverage the attention mechanism to learn the data context from training data corpus. However, these models do not use the …

RDR: the Recap, Deliberate, and Respond Method for Enhanced Language Understanding

2023 · arXiv (Cornell University)

Natural language understanding (NLU) using neural network pipelines often requires additional context that is not solely present in the input data. Through Prior research, it has been evident that NLU benchmarks are susceptible to manipulation …

A Comprehensive Survey on Rare Event Prediction

2024 · ACM Computing Surveys

Rare event prediction involves identifying and forecasting events with a low probability using machine learning (ML) and data analysis. Due to the imbalanced data distributions, where the frequency of common events vastly outweighs that of …