Forbes, Maxwell

The Curious Case of Neural Text Degeneration

Holtzman, A., Buys, J., Du, L., Forbes, M., & Choi, Y. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,304

CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Hessel, J., Holtzman, A., Forbes, M., Le Bras, R., & Choi, Y. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 1,232

Learning to Write with Cooperative Discriminators

Holtzman, A., Buys, J., Forbes, M., Bosselut, A., Golub, D., & Choi, Y. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 192

Social chemistry 101: Learning to reason about social and moral norms

Forbes, M., Hwang, J. D., Shwartz, V., Sap, M., & Choi, Y. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Psychology of Moral and Emotional JudgmentTopic Modeling

Cited by 169

Is GPT-3 text indistinguishable from human text? Scarecrow: A framework for scrutinizing machine text

Dou, Y., Forbes, M., Koncel-Kedziorski, R., Smith, N., & Choi, Y. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 118

Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text

Dou, Y., Forbes, M., Koncel-Kedziorski, R., Smith, N. A., & Choi, Y. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 90

Do Neural Language Representations Learn Physical Commonsense?

Forbes, M., Holtzman, A., & Choi, Y. (2019) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 60