Papers by Taewook Hwang
FEAT: A Preference Feedback Dataset through a Cost-Effective Auto-Generation and Labeling Framework for English AI Tutoring (2025.acl-short)
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| Challenge: | Existing algorithms for teacher feedback generation are time-consuming and costly to generate manually. |
| Approach: | They propose a framework for generating teacher feedback using LLMs and humans . they construct three datasets that are time-consuming and costly to generate manually . results show that incorporating a small portion of DM leads to superior performance . |
| Outcome: | The proposed framework performs better on three datasets compared to human-generated feedback and LLM-generated datasets. |
Perceptual Hallucination in Vision–Language Models: Definition, Analysis and Verification (2026.findings-acl)
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| Challenge: | Recent advances in large language models (LLMs) have dramatically improved text understanding and generation capabilities. |
| Approach: | They define perceptual hallucination as the phenomenon where VLMs generate information as if perceived, despite absent or damaged visual evidence. |
| Outcome: | The proposed model reduces hallucination exposure by 36% on average, with reductions of up to 88%. |