Upadhyay, Shyam

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

TableFormer: Robust Transformer Modeling for Table-Text Encoding

Yang, J., Gupta, A., Upadhyay, S., He, L., Goel, R., & Paul, S. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingMultimodal Machine Learning Applications

Cited by 85

TIMEDIAL: Temporal Commonsense Reasoning in Dialog

Qin, L., Gupta, A., Upadhyay, S., He, L., Choi, Y., & Faruqui, M. (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)

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 59

Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Gupta, A., Xu, J., Upadhyay, S., Yang, D., & Faruqui, M. (2021) · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Topic ModelingNatural Language Processing Techniques

Cited by 22

AutoMix: Automatically Mixing Language Models

Aggarwal, P., Madaan, A., Anand, A., Potharaju, S. P., Mishra, S., Zhou, P., Gupta, A., Rajagopal, D., Kappaganthu, K., Yang, Y., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

How FaR Are Large Language Models From Agents with Theory-of-Mind?

Zhou, P., Madaan, A., Potharaju, S. P., Gupta, A., McKee, K. R., Holtzman, A., Pujara, J., Ren, X., Mishra, S., Nematzadeh, A., et al. (2023) · arXiv

Topic ModelingChild and Animal Learning Development

Cited by 6

Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation

Krishna, S., Krishna, K., Mohananey, A., Schwarcz, S., Stambler, A., Upadhyay, S., & Faruqui, M. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 1