Papers with Multi-agent Framework

1 papers
A Multi-Agent Framework for Feature-Constrained Difficulty Control in Reading Comprehension Item Generation (2026.acl-long)

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Challenge: Existing methods for difficulty-controlled reading comprehension item generation rely on a single agent prompting approach.
Approach: They propose a multi-agent framework for Feature-constrained Item Generation where multiple LLM agents collaborate to generate and iteratively revise items based on intended constraints.
Outcome: The proposed method generates items with monotonically increasing difficulty at higher rates than baselines.

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