Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Aspect-level sentiment analysis (ALSA) is the process of collecting, processing, analyzing,
inferring, and synthesizing subjective sentiments of entities contained in texts at the aspect …

One of the recent best attempts at Text-to-SQL is the pre-trained language model. Due to the
structural property of the SQL queries, the seq2seq model takes the responsibility of parsing …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …

The task of text-to-SQL parsing, which aims at converting natural language questions into
executable SQL queries, has garnered increasing attention in recent years. One of the major …

While sentiment analysis systems try to determine the sentiment polarities of given targets
based on the key opinion expressions in input texts, in implicit sentiment analysis (ISA) the …

Aspect-based sentiment analysis is a fine-grained sentiment analysis task, which needs to
detection the sentiment polarity towards a given aspect. Recently, graph neural models over …

Attention Model has now become an important concept in neural networks that has been
researched within diverse application domains. This survey provides a structured and …