Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for
one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they can …

Multi-party conversations (MPCs) are a more practical and challenging scenario involving
more than two interlocutors. This research topic has drawn significant attention from both …

Multi-turn response selection is a task designed for developing dialogue agents. The
performance on this task has a remarkable improvement with pre-trained language models …

Huge amounts of textual conversations occur online every day, where multiple
conversations take place concurrently. Interleaved conversations lead to difficulties in not …

Conversation disentanglement aims to separate intermingled messages into detached
sessions, which is a fundamental task in understanding multi-party conversations. Existing …

Conversation disentanglement aims to group utterances into detached sessions, which is a
fundamental task in processing multi-party conversations. Existing methods have two main …

In an open-domain dialogue system, the consistent persona is a key factor to generate real
and coherent dialogues. Existing methods suffer from the incomprehensive persona tags …

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

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

Conversation disentanglement, the task to identify separate threads in conversations, is an
important pre-processing step in multi-party conversational NLP applications such as …