Alignment-enriched tuning for patch-level pre-trained document image models
Alignment between image and text has shown promising im provements on patch-level pre-trained document image mod els. However, investigating more effective or finer-grained alignment techniques during pre-training requires a large amount of computation cost and time. Thus, a question natu rally aris...
Saved in:
Main Authors: | WANG, Lei, HE, Jiabang, XU, Xing, LIU, Ning, LIU, Hui |
---|---|
格式: | text |
語言: | English |
出版: |
Institutional Knowledge at Singapore Management University
2023
|
主題: | |
在線閱讀: | https://ink.library.smu.edu.sg/sis_research/9318 https://ink.library.smu.edu.sg/context/sis_research/article/10318/viewcontent/Alignment_Enriched_pv.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Mitigating fine-grained hallucination by fine-tuning large vision-language models with caption rewrites
由: WANG, Lei, et al.
出版: (2024) -
ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction
由: HE, Jiabang, et al.
出版: (2023) -
NumGPT: Improving numeracy ability of generative pre-trained models
由: JIN, Zhihua, et al.
出版: (2023) -
ROME: Evaluating pre-trained vision-language models on reasoning beyond visual common sense
由: ZHOU, Kankan, et al.
出版: (2023) -
Cross-domain graph anomaly detection via anomaly-aware contrastive alignment
由: WANG, Qizhou, et al.
出版: (2023)