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2025 EMNLP EMNLP 2025

HOPE at TSAR 2025 Shared Task Balancing Control and Complexity in Readability-Controlled Text Simplification

AbstractThis paper describes our submissions to the TSAR 2025 Shared Task on Readability-Controlled Text Simplification. We present a comparative study of three architectures a rule-based baseline, a heuristic-driven expert system, and a zero-shot generative T5 pipeline with a semantic guardrail. Our analysis shows a trade-off between the controllability of rule-based systems and the fluency of generative models. In this zero-shot setting, simpler, confined systems achieved superior meaning preservation scores compared to the more powerful but less predictable generative model. We present a diagnostic failure analysis on system outputs, illustrating how different architectures result in distinct error patterns such as under-simplification, information loss via heuristics, and semantic drift.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

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