IntelliCode: A Multi-Agent LLM Tutoring System with Centralized Learner Modeling

Challenge:	Existing LLM tutors lack persistent representations of learner knowledge . current systems provide inconsistent hints, overlook dependencies between concepts .
Approach:	They propose a multi-agent LLM tutoring system that integrates mastery estimates, misconceptions, review schedules, and engagement signals.
Outcome:	The proposed system integrates skill assessment, learner profiling, graduated hinting, curriculum selection, spaced repetition, and engagement monitoring over a shared state under a single-writer policy.

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Robustness in NLP

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Zhiheng Xi, Yiwen Ding, Wenxiang Chen, Boyang Hong, Honglin Guo, Junzhe Wang, Xin Guo, Dingwen Yang, Chenyang Liao, Wei He, Songyang Gao, Lu Chen, Rui Zheng, Yicheng Zou, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang

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