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 …

The necessity for scholarly knowledge mining and management has grown significantly as
academic literature and its linkages to authors produce enormously. Information extraction …

Document-level entity-based extraction (EE), aiming at extracting entity-centric information
such as entity roles and entity relations, is key to automatic knowledge acquisition from text …

As the popularity of large language models (LLMs) has risen over the course of the last year,
led by GPT-3/4 and especially its productization as ChatGPT, we have witnessed the …

Background and Objectives: Text summarization plays an essential role in reducing time
and cost in many domains such as medicine, engineering, etc. On the other hand, manual …

Automatic text summarization is one of the most challenging and interesting problems in
natural language processing (NLP). Text summarization is the process of extracting the most …

Session-based recommendation (SBR) aims to recommend items based on user behaviors
in a session. For the online life service platforms, such as Meituan, both the user's location …

Abstract Knowledge-aware methods have boosted a range of natural language processing
applications over the last decades. With the gathered momentum, knowledge recently has …

Artificial Intelligence (AI) is already changing the way law is being applied, thereby
fundamentally affecting the very core of society. While there is increasing interest in the …

Automatic text summarization has enjoyed great progress over the years and is used in
numerous applications, impacting the lives of many. Despite this development, there is little …