Cover Image

ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Zhiwei, Liu, Boyang, Thompson, Paul, Yang, Kailai, Ananiadou, Sophia
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories
by: Liu, Zhiwei, et al.
Published: (2025)

EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis
by: Liu, Zhiwei, et al.
Published: (2024)

Emotion Detection for Misinformation: A Review
by: Liu, Zhiwei, et al.
Published: (2023)

RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Information
by: Liu, Zhiwei, et al.
Published: (2024)

FMDLlama: Financial Misinformation Detection based on Large Language Models
by: Liu, Zhiwei, et al.
Published: (2024)

Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentiments
by: Liu, Zhiwei, et al.
Published: (2025)

MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models
by: Yang, Kailai, et al.
Published: (2024)

Towards Interpretable Mental Health Analysis with Large Language Models
by: Yang, Kailai, et al.
Published: (2023)

Disentangled VAD Representations via a Variational Framework for Political Stance Detection
by: Xu, Beiyu, et al.
Published: (2025)

MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs
by: Liu, Zhiwei, et al.
Published: (2025)

MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models
by: Yang, Kailai, et al.
Published: (2023)

Implicit Graph, Explicit Retrieval: Towards Efficient and Interpretable Long-horizon Memory for Large Language Models
by: Zhang, Xin, et al.
Published: (2026)

Selective Preference Optimization via Token-Level Reward Function Estimation
by: Yang, Kailai, et al.
Published: (2024)

Assessing the Impact of Conspiracy Theories Using Large Language Models
by: Jiang, Bohan, et al.
Published: (2024)

Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis
by: Yu, Zeping, et al.
Published: (2024)

Neuron-Level Knowledge Attribution in Large Language Models
by: Yu, Zeping, et al.
Published: (2023)

Natural Language Processing for Cardiology: A Narrative Review
by: Yang, Kailai, et al.
Published: (2025)

The Lay Person's Guide to Biomedicine: Orchestrating Large Language Models
by: Luo, Zheheng, et al.
Published: (2024)

EmoBench: Evaluating the Emotional Intelligence of Large Language Models
by: Sabour, Sahand, et al.
Published: (2024)

How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning
by: Yu, Zeping, et al.
Published: (2024)

Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models
by: Yu, Zeping, et al.
Published: (2025)

MentraSuite: Post-Training Large Language Models for Mental Health Reasoning and Assessment
by: Xiao, Mengxi, et al.
Published: (2025)

EmoLLM: Appraisal-Grounded Cognitive-Emotional Co-Reasoning in Large Language Models
by: Zhang, Yifei, et al.
Published: (2026)

Exploring Safety Alignment Evaluation of LLMs in Chinese Mental Health Dialogues via LLM-as-Judge
by: Cai, Yunna, et al.
Published: (2025)

MisSpans: Fine-Grained False Span Identification in Cross-Domain Fake News
by: Liu, Zhiwei, et al.
Published: (2026)

EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding
by: Li, Ao, et al.
Published: (2024)

Conspiracy Frame: a Semiotically-Driven Approach for Conspiracy Theories Detection
by: Piva, Heidi Campana, et al.
Published: (2026)

Religious Bias Landscape in Language and Text-to-Image Models: Analysis, Detection, and Debiasing Strategies
by: Abrar, Ajwad, et al.
Published: (2025)

Are Large Language Models True Healthcare Jacks-of-All-Trades? Benchmarking Across Health Professions Beyond Physician Exams
by: Luo, Zheheng, et al.
Published: (2024)

From n-gram to Attention: How Model Architectures Learn and Propagate Bias in Language Modeling
by: Kabir, Mohsinul, et al.
Published: (2025)

RAAR: Retrieval Augmented Agentic Reasoning for Cross-Domain Misinformation Detection
by: Liu, Zhiwei, et al.
Published: (2026)

Large Language Models in Mental Health Care: a Scoping Review
by: Hua, Yining, et al.
Published: (2024)

Detection of Conspiracy Theories Beyond Keyword Bias in German-Language Telegram Using Large Language Models
by: Pustet, Milena, et al.
Published: (2024)

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
by: Hu, He, et al.
Published: (2025)

Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering
by: Yu, Zeping, et al.
Published: (2024)

Understanding and Mitigating Gender Bias in LLMs via Interpretable Neuron Editing
by: Yu, Zeping, et al.
Published: (2025)

Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs
by: Yu, Zeping, et al.
Published: (2025)

EmoBang: Detecting Emotion From Bengali Texts
by: Maruf, Abdullah Al, et al.
Published: (2025)

ConspirED: A Dataset for Cognitive Traits of Conspiracy Theories and Large Language Model Safety
by: Bates, Luke, et al.
Published: (2025)

EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Prompting
by: Yang, Guanrou, et al.
Published: (2025)