More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

Creating learning models that can exhibit sophisticated reasoning abilities is one of the
greatest challenges in deep learning research, and mathematics is rapidly becoming one of …

We introduce InstructABSA, an instruction learning paradigm for Aspect-Based Sentiment
Analysis (ABSA) subtasks. Our method introduces positive, negative, and neutral examples …

Recently developed large language models (LLMs) have been shown to perform
remarkably well on a wide range of language understanding tasks. But, can they really …

We introduce StableLM 2 1.6 B, the first in a new generation of our language model series.
In this technical report, we present in detail the data and training procedure leading to the …

The rapid advancement of large language models (LLMs) has sparked interest in data
synthesis techniques, aiming to generate diverse and high-quality synthetic datasets …

ChatGPT is a large language model trained on increasingly large datasets to perform
diverse language-based tasks. It is capable of answering multiple-choice questions, such as …

Though state-of-the-art (SOTA) NLP systems have achieved remarkable performance on a
variety of language understanding tasks, they primarily focus on questions that have a …

Named Entity Recognition (NER) has seen significant progress in recent years, with
numerous state-of-the-art (SOTA) models achieving high performance. However, very few …

Pre-training on large corpora of text enables the language models to acquire a vast amount
of factual and commonsense knowledge which allows them to achieve remarkable …