24 citations · 38 across the 7 of their papers we have counts for
7 papers
Beyond "I Don't Know": Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty
Jingyi Ren, Ante Wang, Yunghwei Lai +5
Reliable Large Language Models (LLMs) should abstain when confidence is insufficient. However, prior studies often treat refusal as a generic "I don't know'', failing to distinguis…
The Dialogue That Heals: A Comprehensive Evaluation of Doctor Agents' Inquiry Capability
Linlu Gong, Ante Wang, Yunghwei Lai +2
An effective physician should possess a combination of empathy, expertise, patience, and clear communication when treating a patient. Recent advances have successfully endowed AI d…
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style
Debdeep Sanyal, Agniva Maiti, Umakanta Maharana +4
Effective teaching requires adapting instructional strategies to accommodate the diverse cognitive and behavioral profiles of students, a persistent challenge in education and teac…
Awaking the Slides: A Tuning-free and Knowledge-regulated AI Tutoring System via Language Model Coordination
Daniel Zhang-Li, Zheyuan Zhang, Jifan Yu +8
The vast pre-existing slides serve as rich and important materials to carry lecture knowledge. However, effectively leveraging lecture slides to serve students is difficult due to…
From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Jifan Yu, Zheyuan Zhang, Daniel Zhang-li +30
Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to r…
Simulating Classroom Education with LLM-Empowered Agents
Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu +9
Large language models (LLMs) have been applied across various intelligent educational tasks to assist teaching. While preliminary studies have focused on task-specific, independent…
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
Jifan Yu, Xiaozhi Wang, Shangqing Tu +32
The unprecedented performance of large language models (LLMs) necessitates improvements in evaluations. Rather than merely exploring the breadth of LLM abilities, we believe meticu…