Lauscher, Anne

RedditBias: A real-world resource for bias evaluation and debiasing of conversational language models

Barikeri, S., Lauscher, A., Vulić, I., & Glavaš, G. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 121

What Can Natural Language Processing Do for Peer Review?

Kuznetsov, I., Afzal, O. M., Dercksen, K., Dycke, N., Goldberg, A., Hope, T., Hovy, D., Kummerfeld, J. K., Lauscher, A., Leyton-Brown, K., et al. (2024) · arXiv

Academic Writing and PublishingPublishing and Scholarly Communication

Cited by 6

MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting

Lauscher, A., Ko, B., Kuehl, B., Johnson, S., Jurgens, D., Cohan, A., & Lo, K. (2021) · arXiv

scientometrics and bibliometrics researchTopic Modeling

Cited by 3

Decision-Making with Deliberation: Meta-reviewing as a Document-grounded Dialogue

Purkayastha, S., Dycke, N., Lauscher, A., & Gurevych, I. (2026) · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 2

LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews

Purkayastha, S., Li, Z., Lauscher, A., Qu, L., & Gurevych, I. (2025) · arXiv

Academic Writing and PublishingTopic Modeling

Cited by 1