most citedEmotion fusion for mental illness detection from social media: A survey

86 citations · 210 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20233 cited

A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge

Kailai Yang, Tianlin Zhang, Shaoxiong Ji +1

The context-aware emotional reasoning ability of AI systems, especially in conversations, is of vital importance in applications such as online opinion mining from social media and…

cs.CL202322 cited

Disentangled Variational Autoencoder for Emotion Recognition in Conversations

Kailai Yang, Tianlin Zhang, Sophia Ananiadou

In Emotion Recognition in Conversations (ERC), the emotions of target utterances are closely dependent on their context. Therefore, existing works train the model to generate the r…

cs.CL202316 cited

Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health

Shaoxiong Ji, Tianlin Zhang, Kailai Yang +3

Pretrained language models have been used in various natural language processing applications. In the mental health domain, domain-specific language models are pretrained and relea…

cs.CL202386 cited

Emotion fusion for mental illness detection from social media: A survey

Tianlin Zhang, Kailai Yang, Shaoxiong Ji +1

Mental illnesses are one of the most prevalent public health problems worldwide, which negatively influence people's lives and society's health. With the increasing popularity of s…

cs.CL202383 cited

Cluster-Level Contrastive Learning for Emotion Recognition in Conversations

Kailai Yang, Tianlin Zhang, Hassan Alhuzali +1

A key challenge for Emotion Recognition in Conversations (ERC) is to distinguish semantically similar emotions. Some works utilise Supervised Contrastive Learning (SCL) which uses…