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Jianmo Ni
Jianmo Ni
Zweryfikowany adres z google.com
Tytuł
Cytowane przez
Cytowane przez
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Justifying recommendations using distantly-labeled reviews and fine-grained aspects
J Ni, J Li, J McAuley
Proceedings of the 2019 conference on empirical methods in natural language …, 2019
15292019
Sentence-t5: Scalable sentence encoders from pre-trained text-to-text models
J Ni, GH Abrego, N Constant, J Ma, KB Hall, D Cer, Y Yang
arXiv preprint arXiv:2108.08877, 2021
4512021
Large dual encoders are generalizable retrievers
J Ni, C Qu, J Lu, Z Dai, GH Ábrego, J Ma, VY Zhao, Y Luan, KB Hall, ...
arXiv preprint arXiv:2112.07899, 2021
3482021
Analysis and optimization of droop controller for microgrid system based on small-signal dynamic model
K Yu, Q Ai, S Wang, J Ni, T Lv
IEEE Transactions on Smart Grid 7 (2), 695-705, 2015
3372015
LongT5: Efficient text-to-text transformer for long sequences
M Guo, J Ainslie, D Uthus, S Ontanon, J Ni, YH Sung, Y Yang
arXiv preprint arXiv:2112.07916, 2021
2752021
Transformer memory as a differentiable search index
Y Tay, V Tran, M Dehghani, J Ni, D Bahri, H Mehta, Z Qin, K Hui, Z Zhao, ...
Advances in Neural Information Processing Systems 35, 21831-21843, 2022
2222022
Ext5: Towards extreme multi-task scaling for transfer learning
V Aribandi, Y Tay, T Schuster, J Rao, HS Zheng, SV Mehta, H Zhuang, ...
arXiv preprint arXiv:2111.10952, 2021
2062021
Promptagator: Few-shot dense retrieval from 8 examples
Z Dai, VY Zhao, J Ma, Y Luan, J Ni, J Lu, A Bakalov, K Guu, KB Hall, ...
arXiv preprint arXiv:2209.11755, 2022
1852022
Scaling Up Models and Data with T5X and SeqIO
A Roberts, HW Chung, A Levskaya, G Mishra, J Bradbury, D Andor, ...
https://arxiv.org/abs/2203.17189, 2022
1542022
Generating personalized recipes from historical user preferences
BP Majumder, S Li, J Ni, J McAuley
arXiv preprint arXiv:1909.00105, 2019
1342019
Modeling heart rate and activity data for personalized fitness recommendation
J Ni, L Muhlstein, J McAuley
The World Wide Web Conference, 1343-1353, 2019
1182019
Attributed question answering: Evaluation and modeling for attributed large language models
B Bohnet, VQ Tran, P Verga, R Aharoni, D Andor, LB Soares, M Ciaramita, ...
arXiv preprint arXiv:2212.08037, 2022
1072022
Economic power transaction using coalitional game strategy in micro‐grids
J Ni, Q Ai
IET Generation, Transmission & Distribution 10 (1), 10-18, 2016
1002016
Do llms understand user preferences? evaluating llms on user rating prediction
WC Kang, J Ni, N Mehta, M Sathiamoorthy, L Hong, E Chi, DZ Cheng
arXiv preprint arXiv:2305.06474, 2023
972023
Rankt5: Fine-tuning t5 for text ranking with ranking losses
H Zhuang, Z Qin, R Jagerman, K Hui, J Ma, J Lu, J Ni, X Wang, ...
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
962023
Scalable and accurate dialogue state tracking via hierarchical sequence generation
L Ren, J Ni, J McAuley
arXiv preprint arXiv:1909.00754, 2019
932019
Personalized review generation by expanding phrases and attending on aspect-aware representations
J Ni, J McAuley
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
852018
Addressing marketing bias in product recommendations
M Wan, J Ni, R Misra, J McAuley
Proceedings of the 13th international conference on web search and data …, 2020
732020
Estimating reactions and recommending products with generative models of reviews
J Ni, ZC Lipton, S Vikram, J McAuley
Proceedings of the Eighth International Joint Conference on Natural Language …, 2017
552017
Learning to attend on essential terms: An enhanced retriever-reader model for open-domain question answering
J Ni, C Zhu, W Chen, J McAuley
arXiv preprint arXiv:1808.09492, 2018
522018
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