| Muppet: Massive multi-task representations with pre-finetuning A Aghajanyan, A Gupta, A Shrivastava, X Chen, L Zettlemoyer, S Gupta arXiv preprint arXiv:2101.11038, 2021 | 295 | 2021 |
| Better fine-tuning by reducing representational collapse A Aghajanyan, A Shrivastava, A Gupta, N Goyal, L Zettlemoyer, S Gupta arXiv preprint arXiv:2008.03156, 2020 | 257 | 2020 |
| Chameleon: Mixed-Modal Early-Fusion Foundation Models C Team arXiv preprint arXiv:2405.09818, 2024 | 155* | 2024 |
| Conversational semantic parsing A Aghajanyan, J Maillard, A Shrivastava, K Diedrick, M Haeger, H Li, ... arXiv preprint arXiv:2009.13655, 2020 | 54 | 2020 |
| Layer skip: Enabling early exit inference and self-speculative decoding M Elhoushi, A Shrivastava, D Liskovich, B Hosmer, B Wasti, L Lai, ... arXiv preprint arXiv:2404.16710, 2024 | 49 | 2024 |
| Stop: A dataset for spoken task oriented semantic parsing P Tomasello, A Shrivastava, D Lazar, PC Hsu, D Le, A Sagar, A Elkahky, ... 2022 IEEE Spoken Language Technology Workshop (SLT), 991-998, 2023 | 32 | 2023 |
| Non-autoregressive semantic parsing for compositional task-oriented dialog A Babu, A Shrivastava, A Aghajanyan, A Aly, A Fan, M Ghazvininejad arXiv preprint arXiv:2104.04923, 2021 | 28 | 2021 |
| Cross-lingual transfer learning for intent detection of covid-19 utterances A Arora, A Shrivastava, M Mohit, LSM Lecanda, A Aly | 26 | 2020 |
| Span pointer networks for non-autoregressive task-oriented semantic parsing A Shrivastava, P Chuang, A Babu, S Desai, A Arora, A Zotov, A Aly arXiv preprint arXiv:2104.07275, 2021 | 25 | 2021 |
| Retronlu: Retrieval augmented task-oriented semantic parsing V Gupta, A Shrivastava, A Sagar, A Aghajanyan, D Savenkov arXiv preprint arXiv:2109.10410, 2021 | 20 | 2021 |
| Latency-aware neural architecture search with multi-objective bayesian optimization D Eriksson, PIJ Chuang, S Daulton, P Xia, A Shrivastava, A Babu, S Zhao, ... arXiv preprint arXiv:2106.11890, 2021 | 17 | 2021 |
| MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts XV Lin, A Shrivastava, L Luo, S Iyer, M Lewis, G Gosh, L Zettlemoyer, ... arXiv preprint arXiv:2407.21770, 2024 | 15 | 2024 |
| Deliberation model for on-device spoken language understanding D Le, A Shrivastava, P Tomasello, S Kim, A Livshits, O Kalinli, ML Seltzer arXiv preprint arXiv:2204.01893, 2022 | 14 | 2022 |
| Privately Customizing Prefinetuning to Better Match User Data in Federated Learning C Hou, H Zhan, A Shrivastava, S Wang, S Livshits, G Fanti, D Lazar arXiv preprint arXiv:2302.09042, 2023 | 13 | 2023 |
| Low-resource task-oriented semantic parsing via intrinsic modeling S Desai, A Shrivastava, A Zotov, A Aly arXiv preprint arXiv:2104.07224, 2021 | 11 | 2021 |
| iSeqL: interactive sequence learning A Shrivastava, J Heer Proceedings of the 25th International Conference on Intelligent User …, 2020 | 11 | 2020 |
| Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing A Shrivastava, S Desai, A Gupta, A Elkahky, A Livshits, A Zotov, A Aly arXiv preprint arXiv:2202.00901, 2022 | 7 | 2022 |
| PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs C Hou, A Shrivastava, H Zhan, R Conway, T Le, A Sagar, G Fanti, D Lazar Privacy Regulation and Protection in Machine Learning, 0 | 5* | |
| Muppet: massive multi-task representations with pre-finetuning. 2021 A Aghajanyan, A Gupta, A Shrivastava, X Chen, L Zettlemoyer, S Gupta URL https://arxiv. org/abs/2101.11038, 0 | 5 | |
| Small But Funny: A Feedback-Driven Approach to Humor Distillation S Ravi, P Huber, A Shrivastava, A Sagar, A Aly, V Shwartz, A Einolghozati arXiv preprint arXiv:2402.18113, 2024 | 4 | 2024 |
