Zobrazeno 1 - 10
of 21 270
pro vyhledávání: '"An, Yining"'
As LLMs become increasingly prevalent, it is interesting to consider how ``creative'' these models can be. From cognitive science, creativity consists of at least two key characteristics: \emph{convergent} thinking (purposefulness to achieve a given
Externí odkaz:
http://arxiv.org/abs/2407.09007
Significant focus has been placed on integrating large language models (LLMs) with various tools in developing general-purpose agents. This poses a challenge to LLMs' tool-use capabilities. However, there are evident gaps between existing tool-use ev
Externí odkaz:
http://arxiv.org/abs/2407.08713
Whole-body pose estimation is a challenging task that requires simultaneous prediction of keypoints for the body, hands, face, and feet. Whole-body pose estimation aims to predict fine-grained pose information for the human body, including the face,
Externí odkaz:
http://arxiv.org/abs/2407.08634
Pansharpening aims to generate a high spatial resolution multispectral image (HRMS) by fusing a low spatial resolution multispectral image (LRMS) and a panchromatic image (PAN). The most challenging issue for this task is that only the to-be-fused LR
Externí odkaz:
http://arxiv.org/abs/2407.06633
Autor:
Liu, Jiajun, Ke, Wenjun, Wang, Peng, Wang, Jiahao, Gao, Jinhua, Shang, Ziyu, Li, Guozheng, Xu, Zijie, Ji, Ke, Li, Yining
Continual Knowledge Graph Embedding (CKGE) aims to efficiently learn new knowledge and simultaneously preserve old knowledge. Dominant approaches primarily focus on alleviating catastrophic forgetting of old knowledge but neglect efficient learning f
Externí odkaz:
http://arxiv.org/abs/2407.05705
In this paper, we consider a multi-stage dynamic assortment optimization problem with multi-nomial choice modeling (MNL) under resource knapsack constraints. Given the current resource inventory levels, the retailer makes an assortment decision at ea
Externí odkaz:
http://arxiv.org/abs/2407.05564
This paper focuses on Federated Domain-Incremental Learning (FDIL) where each client continues to learn incremental tasks where their domain shifts from each other. We propose a novel adaptive knowledge matching-based personalized FDIL approach (pFed
Externí odkaz:
http://arxiv.org/abs/2407.05005
Quasi-periodic oscillations in solar flaring emission have been observed over the past few decades. To date, the underpinning processes resulting in the quasi-periodic oscillations remain unknown. In this paper, we report a unique event that exhibits
Externí odkaz:
http://arxiv.org/abs/2407.03639
Autor:
Zhang, Pan, Dong, Xiaoyi, Zang, Yuhang, Cao, Yuhang, Qian, Rui, Chen, Lin, Guo, Qipeng, Duan, Haodong, Wang, Bin, Ouyang, Linke, Zhang, Songyang, Zhang, Wenwei, Li, Yining, Gao, Yang, Sun, Peng, Zhang, Xinyue, Li, Wei, Li, Jingwen, Wang, Wenhai, Yan, Hang, He, Conghui, Zhang, Xingcheng, Chen, Kai, Dai, Jifeng, Qiao, Yu, Lin, Dahua, Wang, Jiaqi
We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that supports long-contextual input and output. IXC-2.5 excels in various text-image comprehension and composition applications, achieving GPT-4V level capabilities
Externí odkaz:
http://arxiv.org/abs/2407.03320
Reinforcement learning continuously optimizes decision-making based on real-time feedback reward signals through continuous interaction with the environment, demonstrating strong adaptive and self-learning capabilities. In recent years, it has become
Externí odkaz:
http://arxiv.org/abs/2407.02539