Papers by Gabriella Skitalinskaya
LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback (2024.acl-long)
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| Challenge: | Creating trusted and safe online spaces for people with different backgrounds and opinions is a challenge for social media platforms. |
| Approach: | They propose a reinforcement learning-based rewriting approach that balances content preservation and appropriateness based on existing classifiers. |
| Outcome: | The proposed approach significantly outperforms baselines including few-shot learning, prompting, and humans. |
To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support (2023.acl-long)
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| Challenge: | assessing whether and how different claims in a text need to be revised is a hard task, especially for novice writers. |
| Approach: | They propose a sampling strategy based on revision distance to capture differences between versions of the same text. |
| Outcome: | The proposed sampling strategy can be done without additional annotations and judgments. |
Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale (2021.eacl-main)
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| Challenge: | Existing research on predicting argument quality based on subjective assessments of human annotators ignores this limitation. |
| Approach: | They propose to compare different revisions of the same claim to assess their quality . they use logistic regression and transformer-based neural networks to learn quality indicators . |
| Outcome: | The proposed tasks show that the learned indicators generalize well across topics. |