Papers by Raymond Liu

2 papers
Using Commonsense Knowledge to Answer Why-Questions (2022.emnlp-main)

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Challenge: Existing approaches to integrating commonsense knowledge into large language models are implicit and explicit.
Approach: They analyze the effects of model size and methods of injecting knowledge into TellMeWhy datasets to determine what aspects of commonsense knowledge are available in large language models.
Outcome: The largest models yield substantial improvements over base models, but the amount of improvement decreases with larger model size.
Analyzing values about gendered language reform in LLMs’ revisions (2025.emnlp-main)

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Challenge: In the past years, LLMs have been used in everyday tasks, especially the formulation and revision of text.
Approach: They examine LLMs' revision of gendered role nouns and their justifications using a prompt set-up to examine their alignment with feminist and trans-inclusive language reforms for English.
Outcome: The proposed revision choices are based on the literature and empirical evidence.

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