Követés
Sheng Zhang
Sheng Zhang
Microsoft Research
E-mail megerősítve itt: microsoft.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
BioGPT: generative pre-trained transformer for biomedical text generation and mining
R Luo, L Sun, Y Xia, T Qin, S Zhang, H Poon, TY Liu
Briefings in bioinformatics 23 (6), bbac409, 2022
8342022
LLaVA-Med: Training a large language-and-vision assistant for biomedicine in one day
C Li, C Wong, S Zhang, N Usuyama, H Liu, J Yang, T Naumann, H Poon, ...
arXiv preprint arXiv:2306.00890, 2023
6532023
Can generalist foundation models outcompete special-purpose tuning? case study in medicine
H Nori, YT Lee, S Zhang, D Carignan, R Edgar, N Fusi, N King, J Larson, ...
arXiv preprint arXiv:2311.16452, 2023
3112023
Biomedclip: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
S Zhang, Y Xu, N Usuyama, H Xu, J Bagga, R Tinn, S Preston, R Rao, ...
arXiv preprint arXiv:2303.00915, 2023
309*2023
ReCoRD: Bridging the gap between human and machine commonsense reading comprehension
S Zhang, X Liu, J Liu, J Gao, K Duh, B Van Durme
arXiv preprint arXiv:1810.12885, 2018
2842018
AMR parsing as sequence-to-graph transduction
S Zhang, X Ma, K Duh, B Van Durme
arXiv preprint arXiv:1905.08704, 2019
1992019
A whole-slide foundation model for digital pathology from real-world data
H Xu, N Usuyama, J Bagga, S Zhang, R Rao, T Naumann, C Wong, ...
Nature 630 (8015), 181-188, 2024
1962024
Universal decompositional semantics on universal dependencies
AS White, D Reisinger, K Sakaguchi, T Vieira, S Zhang, R Rudinger, ...
Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016
1942016
Deep generalized canonical correlation analysis
A Benton, H Khayrallah, B Gujral, DA Reisinger, S Zhang, R Arora
arXiv preprint arXiv:1702.02519, 2017
1932017
Ordinal common-sense inference
S Zhang, R Rudinger, K Duh, B Van Durme
Transactions of the Association of Computational Linguistics, 2017
1362017
Answering natural language questions via phrasal semantic parsing
K Xu, S Zhang, Y Feng, D Zhao
CCF International Conference on Natural Language Processing and Chinese …, 2014
1242014
UniversalNER: Targeted distillation from large language models for open named entity recognition
W Zhou, S Zhang, Y Gu, M Chen, H Poon
arXiv preprint arXiv:2308.03279, 2023
1152023
Context-faithful prompting for large language models
W Zhou, S Zhang, H Poon, M Chen
arXiv preprint arXiv:2303.11315, 2023
1112023
Broad-coverage semantic parsing as transduction
S Zhang, X Ma, K Duh, B Van Durme
arXiv preprint arXiv:1909.02607, 2019
842019
Optimizing bi-encoder for named entity recognition via contrastive learning
S Zhang, H Cheng, J Gao, H Poon
arXiv preprint arXiv:2208.14565, 2022
602022
MT/IE: Cross-lingual open information extraction with neural sequence-to-sequence models
S Zhang, K Duh, B Van Durme
Proceedings of the 15th Conference of the European Chapter of the …, 2017
432017
An Evaluation of PredPatt and Open IE via Stage 1 Semantic Role Labeling
S Zhang, R Rudinger, B Van Durme
IWCS 2017—12th International Conference on Computational Semantics—Short …, 2017
432017
Knowledge-rich self-supervision for biomedical entity linking
S Zhang, H Cheng, S Vashishth, C Wong, J Xiao, X Liu, T Naumann, ...
arXiv preprint arXiv:2112.07887, 2021
422021
Muirbench: A comprehensive benchmark for robust multi-image understanding
F Wang, X Fu, JY Huang, Z Li, Q Liu, X Liu, MD Ma, N Xu, W Zhou, ...
arXiv preprint arXiv:2406.09411, 2024
362024
The universal decompositional semantics dataset and decomp toolkit
AS White, E Stengel-Eskin, S Vashishtha, V Govindarajan, DA Reisinger, ...
arXiv preprint arXiv:1909.13851, 2019
322019
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