Papers by Karin Sevegnani
OTTers: One-turn Topic Transitions for Open-Domain Dialogue (2021.acl-long)
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| Challenge: | a mixed-initiative dialogue system is often purely responsive, make abrupt transitions, or fail to take initiative. |
| Approach: | They propose a task to generate a "bridging" utterance connecting a new topic to the previous conversation turn. |
| Outcome: | The proposed task generates a "bridging" utterance connecting a new topic to the previous topic. |
The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining (2026.acl-long)
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Jiandong Shao, Raphael Tang, Crystina Zhang, Karin Sevegnani, Pontus Stenetorp, Jianfei Yang, Yao Lu
| Challenge: | Existing research suggests that multilingual large language models can achieve impressive cross-lingual understanding despite largely monolingual pretraining. |
| Approach: | They compare a monolingual-only corpus with a standard web corpus that removes all multilingual documents and then retrain the models from scratch under controlled conditions. |
| Outcome: | The results show that removing bilingual data causes translation performance to drop 56% in BLEU, whereas code-switching contributes minimally. |