Sumit Sanghai

According to our database, Sumit Sanghai authored at least 15 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Functional Interpolation for Relative Positions Improves Long Context Transformers.

Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli

CoRR, 2023

MEMORY-VQ: Compression for Tractable Internet-Scale Memory.

Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie

CoRR, 2023

GLIMMER: generalized late-interaction memory reranker.

Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Sumit Sanghai, William W. Cohen, Joshua Ainslie

CoRR, 2023

Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models.

Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai

Proceedings of the International Conference on Machine Learning, 2023

Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute.

Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen

Proceedings of the International Conference on Machine Learning, 2023

GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, Sumit Sanghai

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

CoLT5: Faster Long-Range Transformers with Conditional Computation.

Joshua Ainslie, Tao Lei, Michiel de Jong, Santiago Ontañón, Siddhartha Brahma, Yury Zemlyanskiy, David C. Uthus, Mandy Guo, James Lee-Thorp, Yi Tay, Yun-Hsuan Sung, Sumit Sanghai

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference.

Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

ImPaKT: A Dataset for Open-Schema Knowledge Base Construction.

Luke Vilnis, Zachary Fisher, Bhargav Kanagal, Patrick Murray, Sumit Sanghai

CoRR, 2022

MAVE: A Product Dataset for Multi-source Attribute Value Extraction.

Li Yang, Qifan Wang, Zac Yu, Anand Kulkarni, Sumit Sanghai, Bin Shu, Jon Elsas, Bhargav Kanagal

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Generate-and-Retrieve: Use Your Predictions to Improve Retrieval for Semantic Parsing.

Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

ShopTalk: A System for Conversational Faceted Search.

Gurmeet Manku, James Lee-Thorp, Bhargav Kanagal, Joshua Ainslie, Jingchen Feng, Zach Pearson, Ebenezer Anjorin, Sudeep Gandhe, Ilya Eckstein, Jim Rosswog, Sumit Sanghai, Michael Pohl, Larry Adams, D. Sivakumar

CoRR, 2021

2020

ETC: Encoding Long and Structured Data in Transformers.

Joshua Ainslie, Santiago Ontañón, Chris Alberti, Philip Pham, Anirudh Ravula, Sumit Sanghai

CoRR, 2020

Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach.

Qifan Wang, Li Yang, Bhargav Kanagal, Sumit Sanghai, D. Sivakumar, Bin Shu, Zac Yu, Jon Elsas

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

ETC: Encoding Long and Structured Inputs in Transformers.

Joshua Ainslie, Santiago Ontañón, Chris Alberti, Vaclav Cvicek, Zachary Fisher, Philip Pham, Anirudh Ravula, Sumit Sanghai, Qifan Wang, Li Yang

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020