As large language models continue to advance in Artificial Intelligence (AI), text generation
systems have been shown to suffer from a problematic phenomenon often termed as" …

We introduce TLDR generation, a new form of extreme summarization, for scientific papers.
TLDR generation involves high source compression and requires expert background …

Opinions in the scientific domain can be divergent, leading to controversy or consensus
among reviewers. However, current opinion summarization datasets mostly focus on product …

Recently, opinion summarization, which is the generation of a summary from multiple
reviews, has been conducted in a self-supervised manner by considering a sampled review …

In e-commerce, opinion summarization is the process of condensing the opinions presented
in product reviews. However, the absence of large amounts of supervised datasets presents …

Opinion summarization can facilitate user's decision-making by mining the salient review
information. However, due to the lack of sufficient annotated data, most of the early works …

As the impact of social media gradually escalates, people are more likely to be exposed to
indistinguishable fake news. Therefore, numerous studies have attempted to detect rumors …

Customer reviews are vital for making purchasing decisions in the Information Age. Such
reviews can be automatically summarized to provide the user with an overview of opinions …

We describe the 2021 Key Point Analysis (KPA-2021) shared task on key point analysis that
we organized as a part of the 8th Workshop on Argument Mining (ArgMining 2021) at …

Opinion summarization focuses on generating summaries that reflect popular subjective
information expressed in multiple online reviews. While generated summaries offer general …