153 citations · 730 across the 26 of their papers we have counts for
26 papers
Overview of the PsyDefDetect Shared Task at BioNLP 2026: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations
Hongbin Na, Zimu Wang, Zhaoming Chen +8
We present an overview of PsyDefDetect, the shared task on detecting levels of psychological defense mechanisms in emotional support dialogues, co-located with BioNLP@ACL 2026. Gro…
SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos
Xiyang Huang, Jiawei Lin, Keying Wu +9
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, temporal ordering, and long-context recall, but overlook a harder capability requi…
MiraMind: Benchmarking Reliable Mental Health Reasoning beyond Answer Accuracy
Mengxi Xiao, Kailai Yang, Pengde Zhao +12
Mental-health reasoning with large language models (LLMs) is an evidence-constrained judgment problem: models must transform limited, subjective, and often ambiguous evidence into…
Natural Language Processing for Cardiology: A Narrative Review
Kailai Yang, Yan Leng, Xin Zhang +5
Cardiovascular diseases are becoming increasingly prevalent in modern society, with a profound impact on global health and well-being. These Cardiovascular disorders are complex an…
Exploring Safety Alignment Evaluation of LLMs in Chinese Mental Health Dialogues via LLM-as-Judge
Yunna Cai, Fan Wang, Haowei Wang +5
Evaluating the safety alignment of LLM responses in high-risk mental health dialogues is particularly difficult due to missing gold-standard answers and the ethically sensitive nat…
MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs
Zhiwei Liu, Lingfei Qian, Qianqian Xie +3
Large language models and vision-language models (which we jointly call LMs) have transformed NLP and CV, demonstrating remarkable potential across various fields. However, their c…
Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models
Zhenghao Lin, Zihao Tang, Xiao Liu +31
We introduce Sigma, an efficient large language model specialized for the system domain, empowered by a novel architecture including DiffQKV attention, and pre-trained on our metic…
Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentiments
Zhiwei Liu, Kailai Yang, Eduard Hovy +1
The widespread dissemination of rumors on social media has a significant impact on people's lives, potentially leading to public panic and fear. Rumors often evoke specific sentime…
FMDLlama: Financial Misinformation Detection based on Large Language Models
Zhiwei Liu, Xin Zhang, Kailai Yang +3
The emergence of social media has made the spread of misinformation easier. In the financial domain, the accuracy of information is crucial for various aspects of financial market,…
Selective Preference Optimization via Token-Level Reward Function Estimation
Kailai Yang, Zhiwei Liu, Qianqian Xie +3
Recent advancements in large language model alignment leverage token-level supervisions to perform fine-grained preference optimization. However, existing token-level alignment met…
RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Information
Zhiwei Liu, Kailai Yang, Qianqian Xie +3
Misinformation is prevalent in various fields such as education, politics, health, etc., causing significant harm to society. However, current methods for cross-domain misinformati…
MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models
Kailai Yang, Zhiwei Liu, Qianqian Xie +3
Recent advancements in large language models (LLMs) focus on aligning to heterogeneous human expectations and values via multi-objective preference alignment. However, existing met…
ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model
Zhiwei Liu, Boyang Liu, Paul Thompson +2
The internet has brought both benefits and harms to society. A prime example of the latter is misinformation, including conspiracy theories, which flood the web. Recent advances in…
HealMe: Harnessing Cognitive Reframing in Large Language Models for Psychotherapy
Mengxi Xiao, Qianqian Xie, Ziyan Kuang +5
Large Language Models (LLMs) can play a vital role in psychotherapy by adeptly handling the crucial task of cognitive reframing and overcoming challenges such as shame, distrust, t…
FinBen: A Holistic Financial Benchmark for Large Language Models
Qianqian Xie, Weiguang Han, Zhengyu Chen +31
LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid devel…
EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis
Zhiwei Liu, Kailai Yang, Tianlin Zhang +2
Sentiment analysis and emotion detection are important research topics in natural language processing (NLP) and benefit many downstream tasks. With the widespread application of LL…
Large Language Models in Mental Health Care: a Scoping Review
Yining Hua, Fenglin Liu, Kailai Yang +9
Objectieve:This review aims to deliver a comprehensive analysis of Large Language Models (LLMs) utilization in mental health care, evaluating their effectiveness, identifying chall…
Rethinking Large Language Models in Mental Health Applications
Shaoxiong Ji, Tianlin Zhang, Kailai Yang +2
Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective…
Emotion Detection for Misinformation: A Review
Zhiwei Liu, Tianlin Zhang, Kailai Yang +3
With the advent of social media, an increasing number of netizens are sharing and reading posts and news online. However, the huge volumes of misinformation (e.g., fake news and ru…
MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models
Kailai Yang, Tianlin Zhang, Ziyan Kuang +3
With the development of web technology, social media texts are becoming a rich source for automatic mental health analysis. As traditional discriminative methods bear the problem o…
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…
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…
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…
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…