Papers by David West
Distilling ChatGPT for Explainable Automated Student Answer Assessment (2023.findings-emnlp)
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| Challenge: | Existing automated student answer assessment models lack explainable and faithful feedback. |
| Approach: | They propose a framework that leverages ChatGPT for student answer scoring and rationale generation. |
| Outcome: | The proposed method improves the overall QWK score by 11% compared to ChatGPT. |
Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring (2024.findings-emnlp)
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| Challenge: | Existing methods for generating rationales that justify scoring decisions are not accurate and often contain hallucinated information. |
| Approach: | They propose a framework capable of generating more faithful rationales and matching performance with classifier-based scoring systems. |
| Outcome: | The proposed framework achieves 38% improvement in QWK score compared to prior work . it can be used to match performance with classifier-based scoring systems . |
RED-CT: A Systems Design Methodology for Using LLM-labeled Data to Train and Deploy Edge Linguistic Classifiers (2025.coling-industry)
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| Challenge: | Large language models have improved our ability to rapidly analyze and classify unstructured natural language data. |
| Approach: | They propose a system approach to employing LLMs as imperfect data annotators for downstream supervised learning tasks. |
| Outcome: | The proposed method outperforms LLM-generated labels in six of eight tests and base classifiers in all tests. |