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pro vyhledávání: '"LI Yu-feng"'
Autor:
Li, Zenan, Zhou, Zhi, Yao, Yuan, Li, Yu-Feng, Cao, Chun, Yang, Fan, Zhang, Xian, Ma, Xiaoxing
A critical question about Large Language Models (LLMs) is whether their apparent deficiency in mathematical reasoning is inherent, or merely a result of insufficient exposure to high-quality mathematical data. To explore this, we developed an automat
Externí odkaz:
http://arxiv.org/abs/2412.04857
It is a fundamental question why quantum mechanics employs complex numbers rather than solely real numbers. In this letter, we conduct the first analysis of imaginarity quantification in neutrino flavor and spin-flavor oscillations. As quantum system
Externí odkaz:
http://arxiv.org/abs/2412.01871
Recent learning-to-imitation methods have shown promising results in planning via imitating within the observation-action space. However, their ability in open environments remains constrained, particularly in long-horizon tasks. In contrast, traditi
Externí odkaz:
http://arxiv.org/abs/2411.18201
Neutrinos are neutral in the Standard Model, but they have tiny charge radii generated by radiative corrections. In theories Beyond the Standard Model, neutrinos can also have magnetic and electric moments and small electric charges (millicharges). W
Externí odkaz:
http://arxiv.org/abs/2411.03122
The development of large language models (LLMs) has significantly enhanced the capabilities of multimodal LLMs (MLLMs) as general assistants. However, lack of user-specific knowledge still restricts their application in human's daily life. In this pa
Externí odkaz:
http://arxiv.org/abs/2410.13360
Recent research on fine-tuning vision-language models has demonstrated impressive performance in various downstream tasks. However, the challenge of obtaining accurately labeled data in real-world applications poses a significant obstacle during the
Externí odkaz:
http://arxiv.org/abs/2409.19696
Vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot ability in image classification tasks by aligning text and images but suffer inferior performance compared with task-specific expert models. On the contrary, expert models
Externí odkaz:
http://arxiv.org/abs/2408.11449
Publikováno v:
Frontiers of Nursing, Vol 7, Iss 1, Pp 59-69 (2020)
The aim of this study was to assess the effectiveness of mindfulness meditation (MM) on anxiety, depression, stress and mindfulness in nursing students.
Externí odkaz:
https://doaj.org/article/d57bca9a39424d02ac9245886af3f81f
Pre-trained vision-language models like CLIP have shown powerful zero-shot inference ability via image-text matching and prove to be strong few-shot learners in various downstream tasks. However, in real-world scenarios, adapting CLIP to downstream t
Externí odkaz:
http://arxiv.org/abs/2406.12638
In offline Imitation Learning (IL), one of the main challenges is the \textit{covariate shift} between the expert observations and the actual distribution encountered by the agent, because it is difficult to determine what action an agent should take
Externí odkaz:
http://arxiv.org/abs/2406.12550