Parikh, Ankur

Natural Questions: A benchmark for question answering research

Kwiatkowski, T., Palomaki, J., Redfield, O., Collins, M., Parikh, A., Alberti, C., Epstein, D., Polosukhin, I., Devlin, J., Lee, K., et al. (2019) · Transactions of the Association for Computational Linguistics

Topic ModelingInformation Retrieval and Search Behavior

Cited by 2,069

BLEURT: Learning Robust Metrics for Text Generation

Sellam, T., Das, D., & Parikh, A. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 1,005

BLEURT: Learning Robust Metrics for Text Generation

Sellam, T., Das, D., & Parikh, A. P. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,005

ToTTo: A Controlled Table-To-Text Generation Dataset

Parikh, A., Wang, X., Gehrmann, S., Faruqui, M., Dhingra, B., Yang, D., & Das, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingMultimodal Machine Learning Applications

Cited by 252

ToTTo: A Controlled Table-To-Text Generation Dataset

Parikh, A. P., Wang, X., Gehrmann, S., Faruqui, M., Dhingra, B., Yang, D., & Das, D. (2020) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 252

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Aremu, A., Bosselut, A., Chandu, K. R., Clinciu, M.-A., Das, D., Dhole, K., et al. (2021) · Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)

Natural Language Processing TechniquesTopic Modeling

Cited by 159

Handling Divergent Reference Texts when Evaluating Table-to-Text Generation

Dhingra, B., Faruqui, M., Parikh, A., Chang, M.-W., Das, D., & Cohen, W. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 150

Thieves on Sesame Street! Model Extraction of BERT-based APIs

Krishna, K., Tomar, G. S., Parikh, A. P., Papernot, N., & Iyyer, M. (2019) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 111

Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation

Tian, R., Narayan, S., Sellam, T., & Parikh, A. P. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 60

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Anuoluwapo, A., Bosselut, A., Chandu, K. R., Clinciu, M., Das, D., Dhole, K. D., et al. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 49

Reward Gaming in Conditional Text Generation

Pang, R. Y., Padmakumar, V., Sellam, T., Parikh, A. P., & He, H. (2022) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 2