Zobrazeno 1 - 10
of 3 008
pro vyhledávání: '"Liao,Yuan"'
With increasing revelations of academic fraud, detecting forged experimental images in the biomedical field has become a public concern. The challenge lies in the fact that copy-move targets can include background tissue, small foreground objects, or
Externí odkaz:
http://arxiv.org/abs/2412.10258
Activity-based models in transport are crucial for providing a comprehensive and realistic understanding of individuals' activity-travel patterns. Traditionally, travel surveys have been used to develop these models, but they are often costly and hav
Externí odkaz:
http://arxiv.org/abs/2410.22386
Despite recent advances demonstrating vision-language models' (VLMs) abilities to describe complex relationships in images using natural language, their capability to quantitatively reason about object sizes and distances remains underexplored. In th
Externí odkaz:
http://arxiv.org/abs/2409.09788
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
Autor:
Liao, Yuan, Bian, Jiang, Yun, Yuhui, Wang, Shuo, Zhang, Yubo, Chu, Jiaming, Wang, Tao, Li, Kewei, Li, Yuchen, Li, Xuhong, Ji, Shilei, Xiong, Haoyi
While the field of NL2SQL has made significant advancements in translating natural language instructions into executable SQL scripts for data querying and processing, achieving full automation within the broader data science pipeline - encompassing d
Externí odkaz:
http://arxiv.org/abs/2407.21040
Segregation is a key challenge in promoting more diverse and inclusive cities. Research based on smartphone data has revealed that segregation can extend beyond residential areas into everyday activities like visiting shops and restaurants. The impac
Externí odkaz:
http://arxiv.org/abs/2407.00404
Autor:
Liao, Yuan, Zhang, Yuhong, Wang, Shenghuan, Zhang, Xiruo, Zhang, Yiling, Chen, Wei, Gu, Yuzhe, Huang, Liya
Recent advances in non-invasive EEG technology have broadened its application in emotion recognition, yielding a multitude of related datasets. Yet, deep learning models struggle to generalize across these datasets due to variations in acquisition eq
Externí odkaz:
http://arxiv.org/abs/2406.08081
Due to their ability to anchor into tall urban landforms, such as lampposts or street lights, robotic aerial base stations (RABSs) can create a hyper-flexible wireless multi-hop heterogeneous network to meet the forthcoming green, densified, and dyna
Externí odkaz:
http://arxiv.org/abs/2405.07714
Autor:
Meng, Jian, Liao, Yuan, Anupreetham, Anupreetham, Hasssan, Ahmed, Yu, Shixing, Suh, Han-sok, Hu, Xiaofeng, Seo, Jae-sun
The development of model compression is continuously motivated by the evolution of various neural network accelerators with ASIC or FPGA. On the algorithm side, the ultimate goal of quantization or pruning is accelerating the expensive DNN computatio
Externí odkaz:
http://arxiv.org/abs/2405.01775
Publikováno v:
Phys. Rev. B 110, 235111 (2024)
The subleading corner logarithmic corrections in entanglement entropy (EE) are crucial for revealing universal characteristics of the quantum critical points (QCPs), but they are challenging to detect. Motivated by recent developments in the stable c
Externí odkaz:
http://arxiv.org/abs/2404.13876
Enhancing semantic grounding abilities in Vision-Language Models (VLMs) often involves collecting domain-specific training data, refining the network architectures, or modifying the training recipes. In this work, we venture into an orthogonal direct
Externí odkaz:
http://arxiv.org/abs/2404.06510