Zobrazeno 1 - 10
of 545
pro vyhledávání: '"GUO Ruifeng"'
Autor:
Wei, Jingxuan, Tan, Cheng, Chen, Qi, Wu, Gaowei, Li, Siyuan, Gao, Zhangyang, Sun, Linzhuang, Yu, Bihui, Guo, Ruifeng
We introduce the task of text-to-diagram generation, which focuses on creating structured visual representations directly from textual descriptions. Existing approaches in text-to-image and text-to-code generation lack the logical organization and fl
Externí odkaz:
http://arxiv.org/abs/2411.11916
Autor:
Tan, Cheng, Wei, Jingxuan, Sun, Linzhuang, Gao, Zhangyang, Li, Siyuan, Yu, Bihui, Guo, Ruifeng, Li, Stan Z.
Large language models equipped with retrieval-augmented generation (RAG) represent a burgeoning field aimed at enhancing answering capabilities by leveraging external knowledge bases. Although the application of RAG with language-only models has been
Externí odkaz:
http://arxiv.org/abs/2405.20834
Knowledge distillation, transferring knowledge from a teacher model to a student model, has emerged as a powerful technique in neural machine translation for compressing models or simplifying training targets. Knowledge distillation encompasses two p
Externí odkaz:
http://arxiv.org/abs/2404.14827
In the fields of computer vision and natural language processing, multimodal chart question-answering, especially involving color, structure, and textless charts, poses significant challenges. Traditional methods, which typically involve either direc
Externí odkaz:
http://arxiv.org/abs/2404.01548
Knowledge distillation, a technique for model compression and performance enhancement, has gained significant traction in Neural Machine Translation (NMT). However, existing research primarily focuses on empirical applications, and there is a lack of
Externí odkaz:
http://arxiv.org/abs/2312.08585
Autor:
Tan, Cheng, Wei, Jingxuan, Gao, Zhangyang, Sun, Linzhuang, Li, Siyuan, Guo, Ruifeng, Yu, Bihui, Li, Stan Z.
Multimodal reasoning is a challenging task that requires models to reason across multiple modalities to answer questions. Existing approaches have made progress by incorporating language and visual modalities into a two-stage reasoning framework, sep
Externí odkaz:
http://arxiv.org/abs/2311.14109
Autor:
Guo, Ruifeng, Wei, Jingxuan, Sun, Linzhuang, Yu, Bihui, Chang, Guiyong, Liu, Dawei, Zhang, Sibo, Yao, Zhengbing, Xu, Mingjun, Bu, Liping
With the significant advancements of Large Language Models (LLMs) in the field of Natural Language Processing (NLP), the development of image-text multimodal models has garnered widespread attention. Current surveys on image-text multimodal models ma
Externí odkaz:
http://arxiv.org/abs/2309.15857
Autor:
Wei, Jingxuan, Tan, Cheng, Gao, Zhangyang, Sun, Linzhuang, Li, Siyuan, Yu, Bihui, Guo, Ruifeng, Li, Stan Z.
Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks. While the chain-of-thought (CoT) technique has gained considerable attention,
Externí odkaz:
http://arxiv.org/abs/2307.12626
Publikováno v:
Zhejiang dianli, Vol 43, Iss 6, Pp 88-100 (2024)
Non-intrusive load monitoring （NILM） not only makes the flow of electric energy transparent but also simplifies the installation process of smart meters， effectively reducing the cost of load monitoring. To enhance the accuracy of load recognit
Externí odkaz:
https://doaj.org/article/bcc90c08d7024a148cde771e111c33c9
Autor:
Atiq, Mazen A., Balan, Jagadheshwar, Blackburn, Patrick R., Gross, John M., Voss, Jesse S., Jin, Long, Fadra, Numrah, Davila, Jaime I., Pitel, Beth A., Siqueira Parrilha Terra, Simone Barreto, Minn, Kay T., Jackson, Rory A., Hofich, Christopher D., Willkomm, Kurt S., Peterson, Brenda J., Clausen, Sydney N., Rumilla, Kandelaria M., Gupta, Sounak, Lo, Ying-Chun, Ida, Cris M., Molligan, Jeremy F., Thangaiah, Judith Jebastin, Petersen, Matthew J., Sukov, William R., Guo, Ruifeng, Giannini, Caterina, Schoolmeester, J. Kenneth, II, Fritchie, Karen, Inwards, Carrie Y., Folpe, Andrew L., Oliveira, Andre M., Torres-Mora, Jorge, Kipp, Benjamin R., Halling, Kevin C.
Publikováno v:
In The Journal of Molecular Diagnostics January 2025 27(1):74-95