Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Wu, Xingjiao"'
Autor:
Liu, Kaiyuan, Mei, Jiahao, Zhang, Hengyu, Zhang, Yihuai, Wu, Xingjiao, Dong, Daoguo, He, Liang
Although Chinese calligraphy generation has achieved style transfer, generating calligraphy by specifying the calligrapher, font, and character style remains challenging. To address this, we propose a new Chinese calligraphy generation model 'Moyun'
Externí odkaz:
http://arxiv.org/abs/2410.07618
Detecting cognitive biases in large language models (LLMs) is a fascinating task that aims to probe the existing cognitive biases within these models. Current methods for detecting cognitive biases in language models generally suffer from incomplete
Externí odkaz:
http://arxiv.org/abs/2410.04452
Preference-Based reinforcement learning (PBRL) learns directly from the preferences of human teachers regarding agent behaviors without needing meticulously designed reward functions. However, existing PBRL methods often learn primarily from explicit
Externí odkaz:
http://arxiv.org/abs/2409.07268
When dealing with the task of fine-grained scene image classification, most previous works lay much emphasis on global visual features when doing multi-modal feature fusion. In other words, models are deliberately designed based on prior intuitions a
Externí odkaz:
http://arxiv.org/abs/2407.02769
Detecting stereotypes and biases in Large Language Models (LLMs) is crucial for enhancing fairness and reducing adverse impacts on individuals or groups when these models are applied. Traditional methods, which rely on embedding spaces or are based o
Externí odkaz:
http://arxiv.org/abs/2405.03098
With the increasing prevalence of smartphones and websites, Image Aesthetic Assessment (IAA) has become increasingly crucial. While the significance of attributes in IAA is widely recognized, many attribute-based methods lack consideration for the se
Externí odkaz:
http://arxiv.org/abs/2311.11306
Autor:
Wu, Anran, Xiao, Luwei, Wu, Xingjiao, Yang, Shuwen, Xu, Junjie, Zhuang, Zisong, Xie, Nian, Jin, Cheng, He, Liang
Visually-situated languages such as charts and plots are omnipresent in real-world documents. These graphical depictions are human-readable and are often analyzed in visually-rich documents to address a variety of questions that necessitate complex r
Externí odkaz:
http://arxiv.org/abs/2310.18983
Pre-trained multimodal models have achieved significant success in retrieval-based question answering. However, current multimodal retrieval question-answering models face two main challenges. Firstly, utilizing compressed evidence features as input
Externí odkaz:
http://arxiv.org/abs/2310.09696
Detecting stereotypes and biases in Large Language Models (LLMs) can enhance fairness and reduce adverse impacts on individuals or groups when these LLMs are applied. However, the majority of existing methods focus on measuring the model's preference
Externí odkaz:
http://arxiv.org/abs/2308.10397
Transformer is beneficial for image denoising tasks since it can model long-range dependencies to overcome the limitations presented by inductive convolutional biases. However, directly applying the transformer structure to remove noise is challengin
Externí odkaz:
http://arxiv.org/abs/2304.06346