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pro vyhledávání: '"HU, YIBO"'
Advances in CLIP and large multimodal models (LMMs) have enabled open-vocabulary and free-text segmentation, yet existing models still require predefined category prompts, limiting free-form category self-generation. Most segmentation LMMs also remai
Externí odkaz:
http://arxiv.org/abs/2412.00153
Autor:
Chen, Zhigang, Zhou, Benjia, Huang, Yiqing, Wan, Jun, Hu, Yibo, Shi, Hailin, Liang, Yanyan, Lei, Zhen, Zhang, Du
Sign Language Representation Learning (SLRL) is crucial for a range of sign language-related downstream tasks such as Sign Language Translation (SLT) and Sign Language Retrieval (SLRet). Recently, many gloss-based and gloss-free SLRL methods have bee
Externí odkaz:
http://arxiv.org/abs/2408.09949
Autor:
Chen, Guotao, Sun, Zhonglou, Shi, Wenbo, Wang, Hui, Shi, Guohui, Hu, Yibo, Fan, Huizhong, Wu, Qi, Zhang, Baowei
Publikováno v:
Diversity and Distributions, 2024 Sep 01. 30(9), 1-16.
Externí odkaz:
https://www.jstor.org/stable/48784960
Large language models (LLMs) are transforming the ways the general public accesses and consumes information. Their influence is particularly pronounced in pivotal sectors like healthcare, where lay individuals are increasingly appropriating LLMs as c
Externí odkaz:
http://arxiv.org/abs/2310.13132
Publikováno v:
IEEE Transactions on Multimedia ( Early Access ), 02 October 2023
Point cloud analysis faces computational system overhead, limiting its application on mobile or edge devices. Directly employing small models may result in a significant drop in performance since it is difficult for a small model to adequately captur
Externí odkaz:
http://arxiv.org/abs/2310.05125
Online misinformation poses a global risk with significant real-world consequences. To combat misinformation, current research relies on professionals like journalists and fact-checkers for annotating and debunking misinformation, and develops automa
Externí odkaz:
http://arxiv.org/abs/2310.02095
Autor:
Hu, Yibo, Parolin, Erick Skorupa, Khan, Latifur, Brandt, Patrick T., Osorio, Javier, D'Orazio, Vito J.
Is it possible accurately classify political relations within evolving event ontologies without extensive annotations? This study investigates zero-shot learning methods that use expert knowledge from existing annotation codebook, and evaluates the p
Externí odkaz:
http://arxiv.org/abs/2308.07876
This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this context. ChatEdit is constructed from the CelebA-HQ dataset, incorporating
Externí odkaz:
http://arxiv.org/abs/2303.11108
Publikováno v:
Engineering, Construction and Architectural Management, 2022, Vol. 31, Issue 5, pp. 1835-1856.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ECAM-07-2021-0631
Recent works in cyber deception study how to deter malicious intrusion by generating multiple fake versions of a critical document to impose costs on adversaries who need to identify the correct information. However, existing approaches are context-a
Externí odkaz:
http://arxiv.org/abs/2210.09917