Zobrazeno 1 - 10
of 30 111
pro vyhledávání: '"Wei , Hua"'
Autor:
Yao, Huaiyuan, Da, Longchao, Nandam, Vishnu, Turnau, Justin, Liu, Zhiwei, Pang, Linsey, Wei, Hua
The integration of autonomous vehicles into urban traffic has great potential to improve efficiency by reducing congestion and optimizing traffic flow systematically. In this paper, we introduce CoMAL (Collaborative Multi-Agent LLMs), a framework des
Externí odkaz:
http://arxiv.org/abs/2410.14368
Prompt Tuning has been a popular Parameter-Efficient Fine-Tuning method attributed to its remarkable performance with few updated parameters on various large-scale pretrained Language Models (PLMs). Traditionally, each prompt has been considered indi
Externí odkaz:
http://arxiv.org/abs/2410.12847
The detection of bias in natural language processing (NLP) is a critical challenge, particularly with the increasing use of large language models (LLMs) in various domains. This paper introduces GUS-Net, an innovative approach to bias detection that
Externí odkaz:
http://arxiv.org/abs/2410.08388
Autor:
Shih, Ching-Hung, Peng, Guan-Hao, Lo, Ping-Yuan, Li, Wei-Hua, Xu, Mei-Ling, Chien, Chao-Hsin, Cheng, Shun-Jen
We present a comprehensive theoretical investigation of the strain-modulated excitonic properties of uni-axially strained transition-metal dichalcogenide monolayers (TMD-MLs) by solving the Bethe-Salpeter equation (BSE) established on the basis of fi
Externí odkaz:
http://arxiv.org/abs/2410.03209
Autor:
Da, Longchao, Wang, Rui, Xu, Xiaojian, Bhatia, Parminder, Kass-Hout, Taha, Wei, Hua, Xiao, Cao
Medical imaging is crucial for diagnosing a patient's health condition, and accurate segmentation of these images is essential for isolating regions of interest to ensure precise diagnosis and treatment planning. Existing methods primarily rely on bo
Externí odkaz:
http://arxiv.org/abs/2410.12831
Autor:
Chen, Yi-Hsun, Lo, Ping-Yuan, Boschen, Kyle W., Peng, Guan-Hao, Huang, Chun-Jui, Holtzman, Luke N., Hsu, Chih-En, Hsu, Yung-Ning, Holbrook, Madisen, Wang, Wei-Hua, Barmak, Katayun, Hone, James, Hawrylak, Pawel, Hsueh, Hung-Chung, Davis, Jeffrey A., Cheng, Shun-Jen, Fuhrer, Michael S., Chen, Shao-Yu
In this work, we report a pronounced light upconversion in few-layer transition metal dichalcogenides. Our joint theory-experiment study attributes the upconversion photoluminescence to a resonant exciton-exciton annihilation involving a pair of dark
Externí odkaz:
http://arxiv.org/abs/2409.03387
We introduce SAM4MLLM, an innovative approach which integrates the Segment Anything Model (SAM) with Multi-Modal Large Language Models (MLLMs) for pixel-aware tasks. Our method enables MLLMs to learn pixel-level location information without requiring
Externí odkaz:
http://arxiv.org/abs/2409.10542
Urban traffic is subject to disruptions that cause extended waiting time and safety issues at signalized intersections. While numerous studies have addressed the issue of intelligent traffic systems in the context of various disturbances, traffic sig
Externí odkaz:
http://arxiv.org/abs/2408.09768
Autor:
Chen, Tiejin, Shirke, Prithvi, Chakravarthi, Bharatesh, Vaghela, Arpitsinh, Da, Longchao, Lu, Duo, Yang, Yezhou, Wei, Hua
This paper introduces SynTraC, the first public image-based traffic signal control dataset, aimed at bridging the gap between simulated environments and real-world traffic management challenges. Unlike traditional datasets for traffic signal control
Externí odkaz:
http://arxiv.org/abs/2408.09588
Autor:
Yuan, Hao-Yu, Lei, Wei-Hua
Gamma-ray bursts (GRBs), both from merger of binary compact objects (short GRBs) and collapse of massive stars (long GRBs), are expected to occur in the dense environments, e.g., the accretion disk of active galactic nuclei (AGN). The propagating of
Externí odkaz:
http://arxiv.org/abs/2408.06593