Towards Robust Argumentative Essay Understanding via TIDE: An Interactive Framework with Trial and Debate
Argumentative essays serve as a vital medium for assessing critical thinking and reasoning skills, yet there is limited works on accurately understanding and evaluating such texts via prompt. In this work, we propose TIDE, a novel framework designed to improve criteria-based prompt optimization for argument-related tasks by integrating TrIal and DEbate mechanism. Our method addresses key limitations of criteria-based prompt optimizing by mitigating the influence of noisy training data and enhancing optimization stability. We evaluate TIDE on three core tasks: Automated Essay Scoring, Argument Component Detection, and Argument Relation Identification. Results demonstrate that our framework...
| Authors | Zheqin Yin, Yupei Ren, Yadong Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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