In this work, we investigate a more realistic unsupervised multimodal machine translation
(UMMT) setup, inference-time image-free UMMT, where the model is trained with source-text …

Conversational agents, or commonly known as dialogue systems, have gained escalating
popularity in recent years. Their widespread applications support conversational interactions …

Conversation disentanglement aims to identify and group utterances from a conversation
into separate threads. Existing methods primarily focus on disentangling multi-party …

The joint task of Dialog Sentiment Classification (DSC) and Act Recognition (DAR) aims to
predict the sentiment label and act label for each utterance in a dialog simultaneously …

Group activity recognition (GAR) is an increasingly popular topic in the field of computer
vision. Numerous researchers have proposed a range of methods to achieve outstanding …

We present a new dataset for studying conversation disentanglement in movies and TV
series. While previous work has focused on conversation disentanglement in IRC chatroom …

Dialogue disentanglement aims to detach the chronologically ordered utterances into
several independent sessions. Conversation utterances are essentially organized and …

Unsupervised machine translation (UMT) has achieved notable performance without any
parallel corpora in recent years. Nevertheless, aligning the source language with the target …