2 citations · 3 across the 33 of their papers we have counts for
6 papers · 1 filter
CASTLE: A Comprehensive Benchmark for Evaluating Student-Tailored Personalized Safety in Large Language Models
Rui Jia, Ruiyi Lan, Fengrui Liu +7
Large language models (LLMs) have advanced the development of personalized learning in education. However, their inherent generation mechanisms often produce homogeneous responses…
Cognitive-Level Adaptive Generation via Capability-Aware Retrieval and Style Adaptation
Qingsong Wang, Tao Wu, Wang Lin +4
Large Language Models (LLMs) have demonstrated strong performance in open-ended generation tasks. However, they often struggle to adapt content to users with differing cognitive ca…
Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction
Tao Wu, Jingyuan Chen, Wang Lin +6
Distractors-incorrect yet plausible answer choices in multiple-choice questions (MCQs)-are vital in educational assessments, as they help identify student misconceptions by present…
CoLA: Collaborative Low-Rank Adaptation
Yiyun Zhou, Chang Yao, Jingyuan Chen
The scaling law of Large Language Models (LLMs) reveals a power-law relationship, showing diminishing return on performance as model scale increases. While training LLMs from scrat…
WisdomBot: Tuning Large Language Models with Artificial Intelligence Knowledge
Jingyuan Chen, Tao Wu, Wei Ji +1
Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite the…
MPCODER: Multi-user Personalized Code Generator with Explicit and Implicit Style Representation Learning
Zhenlong Dai, Chang Yao, WenKang Han +3
Large Language Models (LLMs) have demonstrated great potential for assisting developers in their daily development. However, most research focuses on generating correct code, how t…