Papers by Jinchang Zhou

2 papers
Simulating Classroom Education with LLM-Empowered Agents (2025.naacl-long)

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Challenge: Initial studies have focused on task-specific, independent LLM-empowered agents, but the potential of LLMs within a multi-agent collaborative framework for classroom simulation with real user participation remains unexplored.
Approach: They propose a multi-agent classroom simulation teaching framework that recognizes representative class roles and introduces a novel class control mechanism for automatic classroom teaching.
Outcome: The proposed framework can simulate dynamic learning environment for users with active teacher-student and student-studente interactions.
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios (2025.findings-acl)

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Challenge: TableLLM is a robust large language model capable of handling tabular data manipulation tasks.
Approach: They propose a distant supervision method for training which includes a reasoning process extension strategy and a cross-way validation strategy.
Outcome: The proposed model has 8 billion parameters and is capable of handling tabular data tasks.

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