Modeling multi-party conversations (MPCs) with graph neural networks has...
Zero-shot cross-lingual information extraction(IE) aims at constructing ...
Diffusion models have emerged as the new state-of-the-art family of deep...
Addressing the issues of who saying what to whom in multi-party conversa...
This paper describes the system developed by the USTC-NELSLIP team for
S...
Zero-shot cross-lingual named entity recognition (NER) aims at transferr...
Generating natural and informative texts has been a long-standing proble...
Recently, various response generation models for two-party conversations...
Personas are useful for dialogue response prediction. However, the perso...
Recently, various neural models for multi-party conversation (MPC) have
...
Persona can function as the prior knowledge for maintaining the consiste...
Task-oriented conversational modeling with unstructured knowledge access...
The challenges of building knowledge-grounded retrieval-based chatbots l...
Disentanglement is a problem in which multiple conversations occur in th...
In this paper, we study the problem of employing pre-trained language mo...
The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Techn...
We present our work on Track 4 in the Dialogue System Technology Challen...
This paper proposes an utterance-to-utterance interactive matching netwo...
This paper proposes a dually interactive matching network (DIM) for
pres...
We present our work on Track 2 in the Dialog System Technology Challenge...
In this paper, we propose an interactive matching network (IMN) to enhan...
This paper presents an end-to-end response selection model for Track 1 o...