Zobrazeno 1 - 10
of 20 979
pro vyhledávání: '"ZHAO, YI"'
Low-rank adaptation (LoRA) and its mixture-of-experts (MOE) variants are highly effective parameter-efficient fine-tuning (PEFT) methods. However, they introduce significant latency in multi-tenant settings due to the LoRA modules and MOE routers add
Externí odkaz:
http://arxiv.org/abs/2410.18035
Large language models (LLMs) are widely used, but concerns about data contamination challenge the reliability of LLM evaluations. Existing contamination detection methods are often task-specific or require extra prerequisites, limiting practicality.
Externí odkaz:
http://arxiv.org/abs/2410.15005
Passively cooled base stations (PCBSs) have emerged to deliver better cost and energy efficiency. However, passive cooling necessitates intelligent thermal control via traffic management, i.e., the instantaneous data traffic or throughput of a PCBS d
Externí odkaz:
http://arxiv.org/abs/2410.08799
Imitation learning from human motion capture (MoCap) data provides a promising way to train humanoid robots. However, due to differences in morphology, such as varying degrees of joint freedom and force limits, exact replication of human behaviors ma
Externí odkaz:
http://arxiv.org/abs/2410.01968
Publikováno v:
Chinese Physics B 28, 104203, 2019
We present a quantum secure imaging (QSI) scheme based on the phase encoding and weak + vacuum decoy-state BB84 protocol of quantum key distribution (QKD). It allows us to implement a computational ghost imaging (CGI) system with more simplified equi
Externí odkaz:
http://arxiv.org/abs/2410.01172
Autor:
Song, Xiao-Tian, Wang, Dong, Lu, Xiao-Ming, Huang, Da-Jun, Jiang, Di, Li, Li-Xian, Fang, Xi, Zhao, Yi-Bo, Zhou, Liang-Jiang
Publikováno v:
Physical Review A 101,032319,2020
Stability and robustness are important criteria to evaluate the performance of a quantum-key-distribution (QKD) system in real-life applications. However, the inherent birefringence effect of the fiber channel and disturbance caused by the variation
Externí odkaz:
http://arxiv.org/abs/2410.01152
Due to their substantial sizes, large language models (LLMs) are typically deployed within a single-backbone multi-tenant framework. In this setup, a single instance of an LLM backbone must cater to multiple users or tasks through the application of
Externí odkaz:
http://arxiv.org/abs/2409.17834
Autor:
Xu, Zijun, Jin, Rui, Wu, Ke, Zhao, Yi, Zhang, Zhiwei, Zhao, Jieru, Gao, Fei, Gan, Zhongxue, Ding, Wenchao
In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances situational aware
Externí odkaz:
http://arxiv.org/abs/2409.17624
Autor:
Zhao, Yi-Fei, Bove, Allyn, Thompson, David, Hill, James, Xu, Yi, Ren, Yufan, Hassman, Andrea, Zhou, Leming, Wang, Yanshan
Low back pain (LBP) is a leading cause of disability globally. Following the onset of LBP and subsequent treatment, adequate patient education is crucial for improving functionality and long-term outcomes. Despite advancements in patient education st
Externí odkaz:
http://arxiv.org/abs/2409.15260
Emotional intelligence in large language models (LLMs) is of great importance in Natural Language Processing. However, the previous research mainly focus on basic sentiment analysis tasks, such as emotion recognition, which is not enough to evaluate
Externí odkaz:
http://arxiv.org/abs/2409.13359