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Unleashing the Potential of Large Language Models for Predictive Tabular Tasks in Data Science
Despite their proficiency in comprehending natural language, LLMs fall short in dealing with structured tabular data.
Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-view
Analysis and extraction of useful information from legal judgments using computational linguistics was one of the earliest problems posed in the domain of information retrieval.
Exploring the Effects of Data Augmentation for Drivable Area Segmentation
In solving any supervised deep learning problem related to segmentation, the success of the model that one builds depends upon the amount and quality of input training data we use for that model.
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