Barlas Oğuz
Cited by
Cited by
Dense passage retrieval for open-domain question answering
V Karpukhin, B Oğuz, S Min, P Lewis, L Wu, S Edunov, D Chen, W Yih
arXiv preprint arXiv:2004.04906, 2020
MLQA: Evaluating cross-lingual extractive question answering
P Lewis, B Oğuz, R Rinott, S Riedel, H Schwenk
arXiv preprint arXiv:1910.07475, 2019
Unik-qa: Unified representations of structured and unstructured knowledge for open-domain question answering
B Oguz, X Chen, V Karpukhin, S Peshterliev, D Okhonko, M Schlichtkrull, ...
arXiv preprint arXiv:2012.14610, 2020
Llm-qat: Data-free quantization aware training for large language models
Z Liu, B Oguz, C Zhao, E Chang, P Stock, Y Mehdad, Y Shi, ...
arXiv preprint arXiv:2305.17888, 2023
3dgen: Triplane latent diffusion for textured mesh generation
A Gupta, W Xiong, Y Nie, I Jones, B Oğuz
arXiv preprint arXiv:2303.05371, 2023
Effective long-context scaling of foundation models
W Xiong, J Liu, I Molybog, H Zhang, P Bhargava, R Hou, L Martin, ...
arXiv preprint arXiv:2309.16039, 2023
Neurips 2020 efficientqa competition: Systems, analyses and lessons learned
S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ...
NeurIPS 2020 Competition and Demonstration Track, 86-111, 2021
Multi-task retrieval for knowledge-intensive tasks
J Maillard, V Karpukhin, F Petroni, W Yih, B Oğuz, V Stoyanov, G Ghosh
arXiv preprint arXiv:2101.00117, 2021
Domain-matched pre-training tasks for dense retrieval
B Oğuz, K Lakhotia, A Gupta, P Lewis, V Karpukhin, A Piktus, X Chen, ...
arXiv preprint arXiv:2107.13602, 2021
Answering complex open-domain questions with multi-hop dense retrieval
W Xiong, XL Li, S Iyer, J Du, P Lewis, WY Wang, Y Mehdad, W Yih, ...
arXiv preprint arXiv:2009.12756, 2020
Salient phrase aware dense retrieval: can a dense retriever imitate a sparse one?
X Chen, K Lakhotia, B Oğuz, A Gupta, P Lewis, S Peshterliev, Y Mehdad, ...
arXiv preprint arXiv:2110.06918, 2021
How to train your dragon: Diverse augmentation towards generalizable dense retrieval
SC Lin, A Asai, M Li, B Oguz, J Lin, Y Mehdad, W Yih, X Chen
arXiv preprint arXiv:2302.07452, 2023
The web is your oyster-knowledge-intensive NLP against a very large web corpus
A Piktus, F Petroni, V Karpukhin, D Okhonko, S Broscheit, G Izacard, ...
arXiv preprint arXiv:2112.09924, 2021
Bit: Robustly binarized multi-distilled transformer
Z Liu, B Oguz, A Pappu, L Xiao, S Yih, M Li, R Krishnamoorthi, Y Mehdad
Advances in neural information processing systems 35, 14303-14316, 2022
Accelerating recurrent neural network training via two stage classes and parallelization
Z Huang, G Zweig, M Levit, B Dumoulin, B Oguz, S Chang
2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 326-331, 2013
Multilingual seq2seq training with similarity loss for cross-lingual document classification
K Yu, H Li, B Oguz
Proceedings of the third workshop on representation learning for NLP, 175-179, 2018
Stable distributed P2P protocols based on random peer sampling
B Oǧuz, V Anantharam, I Norros
IEEE/ACM Transactions on Networking (TON) 23 (5), 1444-1456, 2015
Hierarchical video-moment retrieval and step-captioning
A Zala, J Cho, S Kottur, X Chen, B Oguz, Y Mehdad, M Bansal
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
Incremental utterance decoder combination for efficient and accurate decoding
S Chang, M Levit, A Lahiri, B Oguz, B Dumoulin
US Patent 9,922,654, 2018
Joint verification and reranking for open fact checking over tables
M Schlichtkrull, V Karpukhin, B Oğuz, M Lewis, W Yih, S Riedel
arXiv preprint arXiv:2012.15115, 2020
The system can't perform the operation now. Try again later.
Articles 1–20