Stanovsky, Gabriel

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., & Gardner, M. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 393

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., & Gardner, M. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 238

State of What Art? A Call for Multi-Prompt LLM Evaluation

Mizrahi, M., Kaplan, G., Malkin, D., Dror, R., Shahaf, D., & Stanovsky, G. (2024) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 113

Evaluating Question Answering Evaluation

Chen, A., Stanovsky, G., Singh, S., & Gardner, M. (2019) · Proceedings of the 2nd Workshop on Machine Reading for Question Answering

Topic ModelingNatural Language Processing Techniques

Cited by 105

Collecting a large-scale gender bias dataset for coreference resolution and machine translation

Levy, S., Lazar, K., & Stanovsky, G. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 41

Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images

Bitton-Guetta, N., Bitton, Y., Hessel, J., Schmidt, L., Elovici, Y., Stanovsky, G., & Schwartz, R. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 37

Cross-document Coreference Resolution over Predicted Mentions

Cattan, A., Eirew, A., Stanovsky, G., Joshi, M., & Dagan, I. (2021) · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Natural Language Processing TechniquesTopic Modeling

Cited by 29

K-QA: A Real-World Medical Q&A Benchmark

Manes, I., Ronn, N., Cohen, D., Ber, R. I., Horowitz-Kugler, Z., & Stanovsky, G. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 17

Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer

Simhi, A., Itzhak, I., Barez, F., Stanovsky, G., & Belinkov, Y. (2025) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 8