The information age enables people to obtain news online through various channels, yet in
the meanwhile making false news spread at unprecedented speed. Fake news exerts …

A transformer is the foundational architecture behind large language models designed to
handle sequential data by using mechanisms of self‐attention to weigh the importance of …

Accurate segmentation of organs or lesions from medical images is crucial for reliable
diagnosis of diseases and organ morphometry. In recent years, convolutional encoder …

We study knowledge-grounded dialogue generation with pre-trained language models. To
leverage the redundant external knowledge under capacity constraint, we propose …

Predicting the price movement of finance securities like stocks is an important but
challenging task, due to the uncertainty of financial markets. In this paper, we propose a …

Conversational recommender systems (CRS) aim to recommend high-quality items to users
through interactive conversations. To develop an effective CRS, the support of high-quality …

Emotion recognition has gained prominence in diverse applications ranging from safe
driving and e-commerce to healthcare. Traditional approaches have often relied on single …

Currently, researchers have paid great attention to retrieval-based dialogues in open-
domain. In particular, people study the problem by investigating context-response matching …

We consider context-response matching with multiple types of representations for multi-turn
response selection in retrieval-based chatbots. The representations encode semantics of …

Continual relation extraction (CRE) aims to continuously train a model on data with new
relations while avoiding forgetting old ones. Some previous work has proved that storing a …