Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary
input modality to direct manipulation for visual analytics can provide an engaging user …

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

Text-to-SQL parsing, which aims at converting natural language instructions into executable
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …

There is currently a significant gap between the performance of fine-tuned models and
prompting approaches using Large Language Models (LLMs) on the challenging task of text …

Large language models (LLMs) have emerged as a new paradigm for Text-to-SQL task.
However, the absence of a systematical benchmark inhibits the development of designing …

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 …

Revealing the underlying causal mechanisms in the real world is the key to the development
of science. Despite the progress in the past decades, traditional causal discovery …

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 …

Language models have shown promising performance on the task of translating natural
language questions into SQL queries (Text-to-SQL). However, most of the state-of-the-art …

Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-
based natural language (NL) understanding tasks. Such models are typically trained on free …