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cs.CL2025
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…
cs.CL2025
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…
cs.CL2025
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…