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20212024
most citedRevisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition

17 citations · 42 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.CL2024

A Survey on Neural Question Generation: Methods, Applications, and Prospects

Shasha Guo, Lizi Liao, Cuiping Li +1

In this survey, we present a detailed examination of the advancements in Neural Question Generation (NQG), a field leveraging neural network techniques to generate relevant questio…

cs.CL2023★ 12 cited

Building Emotional Support Chatbots in the Era of LLMs

Zhonghua Zheng, Lizi Liao, Yang Deng +1

The integration of emotional support into various conversational scenarios presents profound societal benefits, such as social interactions, mental health counseling, and customer…

cs.CL2023★ 17 cited

Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition

Bobo Li, Hao Fei, Lizi Liao +5

It has been a hot research topic to enable machines to understand human emotions in multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion analysis i…

cs.CL2023

Revisiting Conversation Discourse for Dialogue Disentanglement

Bobo Li, Hao Fei, Fei Li +5

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

cs.CL2023★ 1 cited

Actively Discovering New Slots for Task-oriented Conversation

Yuxia Wu, Tianhao Dai, Zhedong Zheng +1

Existing task-oriented conversational search systems heavily rely on domain ontologies with pre-defined slots and candidate value sets. In practical applications, these prerequisit…

cs.CL2022★ 7 cited

DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis

Bobo Li, Hao Fei, Fei Li +8

The rapid development of aspect-based sentiment analysis (ABSA) within recent decades shows great potential for real-world society. The current ABSA works, however, are mostly limi…

cs.CL2022

Conversation Disentanglement with Bi-Level Contrastive Learning

Chengyu Huang, Zheng Zhang, Hao Fei +1

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