Papers by Xiaotian Su

2 papers
Unraveling Downstream Gender Bias from Large Language Models: A Study on AI Educational Writing Assistance (2023.findings-emnlp)

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Challenge: Large Language Models (LLMs) are increasingly utilized in educational tasks such as providing writing suggestions to students.
Approach: They conduct a large-scale user study with 231 students writing business case peer reviews in german.
Outcome: The proposed model does not carry bias in the feedback loops of the students .
Closing the Loop: Learning to Generate Writing Feedback via Language Model Simulated Student Revisions (2024.emnlp-main)

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Challenge: Recent advances in language models (LMs) have made it possible to automatically generate feedback that is actionable and well-aligned with human-specified attributes.
Approach: They propose a tool that PROduces Feedback via learning from LM simulated student revisions and propose to iteratively optimize the feedback generator by directly maximizing the effectiveness of students’ overall revising performance.
Outcome: The proposed approach surpasses baseline methods in effectiveness of improving students’ writing and demonstrates enhanced pedagogical values, even though it was not explicitly trained for this aspect.

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