5 papers
EduRiskX: A Neuro-Symbolic Framework with F-Logic Reasoning for Early Academic Risk Prediction
Yu Fu, Yongqi Kang, Yong Zhao +1
Predicting students' academic risk in online education is crucial for enabling timely interventions that can improve retention and learning outcomes. However, existing models often…
CalBrief: A Pilot Diagnostic Benchmark for Evidence-Calibrated Scientific Briefing with Large Language Models
Yu Fu, Yongqi Kang, Yong Zhao
Large language models (LLMs) are increasingly used as research assistants, yet it remains unclear whether they can calibrate research takeaways to the strength and scope of the sup…
X-MADAM-RAG: Diagnosing and Handling Chinese-English Evidence Conflict in Retrieval-Augmented Generation
Yongqi Kang, Yu Fu, Yong Zhao
Retrieval-augmented generation (RAG) systems may receive evidence that is not merely noisy but mutually contradictory. This issue becomes particularly salient in multilingual setti…
Aligning Large Language Models for Faithful Integrity Against Opposing Argument
Yong Zhao, Yang Deng, See-Kiong Ng +1
Large Language Models (LLMs) have demonstrated impressive capabilities in complex reasoning tasks. However, they can be easily misled by unfaithful arguments during conversations,…
Knowledge Boundary of Large Language Models: A Survey
Moxin Li, Yong Zhao, Wenxuan Zhang +5
Although large language models (LLMs) store vast amount of knowledge in their parameters, they still have limitations in the memorization and utilization of certain knowledge, lead…