6 papers
MisSpans: Fine-Grained False Span Identification in Cross-Domain Fake News
Zhiwei Liu, Paul Thompson, Jiaqi Rong +5
Online misinformation is increasingly pervasive, yet most existing benchmarks and methods evaluate veracity at the level of whole claims or paragraphs using coarse binary labels, o…
RAAR: Retrieval Augmented Agentic Reasoning for Cross-Domain Misinformation Detection
Zhiwei Liu, Runteng Guo, Baojie Qu +4
Cross-domain misinformation detection is challenging, as misinformation arises across domains with substantial differences in knowledge and discourse. Existing methods often rely o…
DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation
Enze Zhang, Jiaying Wang, Mengxi Xiao +7
Large language models (LLMs) have substantially advanced machine translation (MT), yet their effectiveness in translating web novels remains unclear. Existing benchmarks rely on su…
From Scores to Skills: A Cognitive Diagnosis Framework for Evaluating Financial Large Language Models
Ziyan Kuang, Feiyu Zhu, Maowei Jiang +8
Large Language Models (LLMs) have shown promise for financial applications, yet their suitability for this high-stakes domain remains largely unproven due to inadequacies in existi…
MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis
Mengxi Xiao, Ben Liu, He Li +5
The application of AI in psychiatric diagnosis faces significant challenges, including the subjective nature of mental health assessments, symptom overlap across disorders, and pri…
Retrieval-augmented Large Language Models for Financial Time Series Forecasting
Mengxi Xiao, Zihao Jiang, Lingfei Qian +10
Accurately forecasting stock price movements is critical for informed financial decision-making, supporting applications ranging from algorithmic trading to risk management. Howeve…