Yury Zemlyanskiy

According to our database, Yury Zemlyanskiy authored at least 13 papers between 2018 and 2023.

Collaborative distances:

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

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

Mention Memory: incorporating textual knowledge into Transformers through entity mention attention.

Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen

Proceedings of the Tenth International Conference on Learning Representations, 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

ReadTwice: Reading Very Large Documents with Memories.

Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections.

Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2019

Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text.

Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen, Thomas Schnake, Marius Kloft

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner.

Yury Zemlyanskiy, Fei Sha

Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018