The increasing volume of user-generated content on the web has made sentiment analysis
an important tool for the extraction of information about the human emotional state. A current …

With the constantly growing number of reviews and other sentiment-bearing texts on the
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …

Abstract Natural Language Processing (NLP) is a branch of artificial intelligence that
involves the design and implementation of systems and algorithms able to interact through …

In this paper, we introduce NLP resources for 11 major Indian languages from two major
language families. These resources include:(a) large-scale sentence-level monolingual …

Large language models are commonly trained on a mixture of filtered web data and
curated``high-quality''corpora, such as social media conversations, books, or technical …

Node classification is a classical graph representation learning task on which Graph Neural
Networks (GNNs) have recently achieved strong results. However, it is often believed that …

Transfer learning, where a model is first pre-trained on a data-rich task before being fine-
tuned on a downstream task, has emerged as a powerful technique in natural language …

We propose BERTScore, an automatic evaluation metric for text generation. Analogously to
common metrics, BERTScore computes a similarity score for each token in the candidate …

Language models are ubiquitous in current NLP, and their multilingual capacity has recently
attracted considerable attention. However, current analyses have almost exclusively focused …

Pre-training text representations have led to significant improvements in many areas of
natural language processing. The quality of these models benefits greatly from the size of …