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Yury Zemlyanskiy
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2020 – today
- 2024
- [c12]Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie:
MEMORY-VQ: Compression for Tractable Internet-Scale Memory. NAACL (Short Papers) 2024: 737-744 - 2023
- [c11]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. ACL (Findings) 2023: 11534-11547 - [c10]Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, Sumit Sanghai:
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints. EMNLP 2023: 4895-4901 - [c9]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:
CoLT5: Faster Long-Range Transformers with Conditional Computation. EMNLP 2023: 5085-5100 - [c8]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. ICML 2023: 7329-7342 - [c7]Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai:
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models. ICML 2023: 35120-35136 - [i12]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. CoRR abs/2301.10448 (2023) - [i11]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:
CoLT5: Faster Long-Range Transformers with Conditional Computation. CoRR abs/2303.09752 (2023) - [i10]Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, Sumit Sanghai:
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints. CoRR abs/2305.13245 (2023) - [i9]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Sumit Sanghai, William W. Cohen, Joshua Ainslie:
GLIMMER: generalized late-interaction memory reranker. CoRR abs/2306.10231 (2023) - [i8]Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie:
MEMORY-VQ: Compression for Tractable Internet-Scale Memory. CoRR abs/2308.14903 (2023) - 2022
- [c6]Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha:
Generate-and-Retrieve: Use Your Predictions to Improve Retrieval for Semantic Parsing. COLING 2022: 4946-4951 - [c5]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. ICLR 2022 - [i7]Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha:
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing. CoRR abs/2209.14899 (2022) - [i6]Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Passos, Sumit Sanghai:
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models. CoRR abs/2210.15458 (2022) - [i5]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. CoRR abs/2212.08153 (2022) - 2021
- [c4]Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein:
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. EACL 2021: 2540-2549 - [c3]Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha:
ReadTwice: Reading Very Large Documents with Memories. NAACL-HLT 2021: 5189-5195 - [i4]Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein:
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. CoRR abs/2102.13247 (2021) - [i3]Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha:
ReadTwice: Reading Very Large Documents with Memories. CoRR abs/2105.04241 (2021) - [i2]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. CoRR abs/2110.06176 (2021)
2010 – 2019
- 2019
- [c2]Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen
, Thomas Schnake, Marius Kloft:
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text. ACL (1) 2019: 4061-4071 - 2018
- [c1]Yury Zemlyanskiy, Fei Sha:
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoNLL 2018: 551-561 - [i1]Yury Zemlyanskiy, Fei Sha:
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoRR abs/1808.07104 (2018)
Coauthor Index

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last updated on 2024-10-04 19:55 CEST by the dblp team
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