Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …

Computational argumentation has become an essential tool in various fields, including
artificial intelligence, law, and public policy. It is an emerging research field in natural …

The increasing capacities of large language models (LLMs) present an unprecedented
opportunity to scale up data analytics in the humanities and social sciences, augmenting …

The unparalleled performance of closed-sourced ChatGPT has sparked efforts towards its
democratization, with notable strides made by leveraging real user and ChatGPT dialogues …

Topic segmentation is critical for obtaining structured long documents and improving
downstream tasks like information retrieval. Due to its ability of automatically exploring clues …

Dialogue discourse parsing aims to reflect the relation-based structure of dialogue by
establishing discourse links according to discourse relations. To alleviate data sparsity …

This paper provides the first discourse parsing experiments with a large language model
(LLM) finetuned on corpora annotated in the style of SDRT (Segmented Discourse …

Discourse parsing in multi-party dialogue aims to extract the relationships between
elementary discourse units (EDUs) such as arguments and utterances, and has numerous …

In modern commercial systems, including Recommendation, Ranking, and E-Commerce
platforms, there is a trend towards improving customer experiences by incorporating …