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pro vyhledávání: '"YAN YAN"'
Recent advancements in 3D Large Language Models (3DLLMs) have highlighted their potential in building general-purpose agents in the 3D real world, yet challenges remain due to the lack of high-quality robust instruction-following data, leading to lim
Externí odkaz:
http://arxiv.org/abs/2410.00255
Autor:
Shang, Yuzhang, Xu, Bingxin, Kang, Weitai, Cai, Mu, Li, Yuheng, Wen, Zehao, Dong, Zhen, Keutzer, Kurt, Lee, Yong Jae, Yan, Yan
Advancements in Large Language Models (LLMs) inspire various strategies for integrating video modalities. A key approach is Video-LLMs, which incorporate an optimizable interface linking sophisticated video encoders to LLMs. However, due to computati
Externí odkaz:
http://arxiv.org/abs/2409.12963
Diffusion models (DMs) have demonstrated exceptional generative capabilities across various areas, while they are hindered by slow inference speeds and high computational demands during deployment. The most common way to accelerate DMs involves reduc
Externí odkaz:
http://arxiv.org/abs/2409.03550
Dataset distillation (DD) aims to distill a small, information-rich dataset from a larger one for efficient neural network training. However, existing DD methods struggle with long-tailed datasets, which are prevalent in real-world scenarios. By inve
Externí odkaz:
http://arxiv.org/abs/2408.14506
We extend the parity doublet model for hadronic matter and study the possible presence of quark matter inside the cores of neutron stars with the Nambu-Jona-Lasinio (NJL) model. Considering the uncertainties of the QCD phase diagram and the location
Externí odkaz:
http://arxiv.org/abs/2408.05687
Recent advancements in Chain-of-Thoughts (CoT) and Program-of-Thoughts (PoT) methods have greatly enhanced language models' mathematical reasoning capabilities, facilitating their integration into instruction tuning datasets with LLMs. However, exist
Externí odkaz:
http://arxiv.org/abs/2408.07089
Autor:
Patterson, J. R.
Publikováno v:
World Literature Today, 2021 Oct 01. 95(4), 88-89.
Externí odkaz:
https://www.jstor.org/stable/10.7588/worllitetoda.95.4.0088
Autor:
Shi, Rui, Brewer, Michael K., Chan, Carol Yan Yan, Chuss, David T., Couto, Jullianna Denes, Eimer, Joseph R., Karakla, John, Shukawa, Koji, Valle, Deniz A. N., Appel, John W., Bennett, Charles L., Dahal, Sumit, Essinger-Hileman, Thomas, Marriage, Tobias A., Petroff, Matthew A., Rostem, Karwan, Wollack, Edward J.
Front-end polarization modulation enables improved polarization measurement stability by modulating the targeted signal above the low-frequency $1/f$ drifts associated with atmospheric and instrumental instabilities and diminishes the impact of instr
Externí odkaz:
http://arxiv.org/abs/2407.08912
Deep learning has made remarkable progress recently, largely due to the availability of large, well-labeled datasets. However, the training on such datasets elevates costs and computational demands. To address this, various techniques like coreset se
Externí odkaz:
http://arxiv.org/abs/2407.07268
Semi-Supervised Visual Grounding (SSVG) is a new challenge for its sparse labeled data with the need for multimodel understanding. A previous study, RefTeacher, makes the first attempt to tackle this task by adopting the teacher-student framework to
Externí odkaz:
http://arxiv.org/abs/2407.03251