Meetings are a key component of human collaboration. As increasing numbers of meetings
are recorded and transcribed, meeting summaries have become essential to remind those …

The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …

Abstract We survey Natural Language Processing (NLP) approaches to summarizing,
simplifying, and generating patents' text. While solving these tasks has important practical …

Automatic License Plate Recognition (ALPR) systems have shown remarkable performance
on license plates (LPs) from multiple regions due to advances in deep learning and the …

To mitigate potential risks associated with language models (LMs), recent AI detection
research proposes incorporating watermarks into machine-generated text through random …

The task of natural language table retrieval (NLTR) seeks to retrieve semantically relevant
tables based on natural language queries. Existing learning systems for this task often treat …

Abstractive summarization is a technique that allows for extracting condensed meanings
from long texts, with a variety of potential practical applications. Nonetheless, today's …

State-of-the-art summarization systems are trained and evaluated on massive datasets
scraped from the web. Despite their prevalence, we know very little about the underlying …

With the continuous upgrading of the summarization systems driven by deep neural
networks, researchers have higher requirements on the quality of the generated summaries …

Legal professionals frequently encounter long legal judgments that hold critical insights for
their work. While recent advances have led to automated summarization solutions for legal …