Zobrazeno 1 - 10
of 25 884
pro vyhledávání: '"A, Jinlin"'
Autor:
ZHONG, Guoqing1
Publikováno v:
Journal of Landscape Research. Apr2021, Vol. 13 Issue 2, p36-41. 6p.
Surgical interventions, particularly in neurology, represent complex and high-stakes scenarios that impose substantial cognitive burdens on surgical teams. Although deliberate education and practice can enhance cognitive capabilities, surgical traini
Externí odkaz:
http://arxiv.org/abs/2412.05187
Autor:
Zhang, Yuxiang, Wu, Shangxi, Yang, Yuqi, Shu, Jiangming, Xiao, Jinlin, Kong, Chao, Sang, Jitao
The technical report introduces O1-CODER, an attempt to replicate OpenAI's o1 model with a focus on coding tasks. It integrates reinforcement learning (RL) and Monte Carlo Tree Search (MCTS) to enhance the model's System-2 thinking capabilities. The
Externí odkaz:
http://arxiv.org/abs/2412.00154
While text-to-image generation has been extensively studied, generating images from scene graphs remains relatively underexplored, primarily due to challenges in accurately modeling spatial relationships and object interactions. To fill this gap, we
Externí odkaz:
http://arxiv.org/abs/2411.15435
Large language models (LLMs) are often equipped with multi-sample decoding strategies. An LLM implicitly defines an arithmetic code book, facilitating efficient and embarrassingly parallelizable \textbf{arithmetic sampling} to produce multiple sample
Externí odkaz:
http://arxiv.org/abs/2411.06251
Autor:
Choi, Minho, Xiang, Jinlin, Wirth-Singh, Anna, Baek, Seung-Hwan, Shlizerman, Eli, Majumdar, Arka
Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand substantial computational resources, often hindering real-time operati
Externí odkaz:
http://arxiv.org/abs/2411.02697
Bayesian reasoning in linear mixed-effects models (LMMs) is challenging and often requires advanced sampling techniques like Markov chain Monte Carlo (MCMC). A common approach is to write the model in a probabilistic programming language and then sam
Externí odkaz:
http://arxiv.org/abs/2410.24079
Large Language Models (LLMs) are proficient at retrieving single facts from extended contexts, yet they struggle with tasks requiring the simultaneous retrieval of multiple facts, especially during generation. This paper identifies a novel "lost-in-t
Externí odkaz:
http://arxiv.org/abs/2410.21012
Dimensionality reduction (DR) plays a crucial role in various fields, including data engineering and visualization, by simplifying complex datasets while retaining essential information. However, the challenge of balancing DR accuracy and interpretab
Externí odkaz:
http://arxiv.org/abs/2410.19504
Accurate and complete segmentation of airways in chest CT images is essential for the quantitative assessment of lung diseases and the facilitation of pulmonary interventional procedures. Although deep learning has led to significant advancements in
Externí odkaz:
http://arxiv.org/abs/2410.18456