Zobrazeno 1 - 10
of 21 061
pro vyhledávání: '"WANG, Huan"'
Autor:
Wang, Huan, Tan, Feitong, Bai, Ziqian, Zhang, Yinda, Liu, Shichen, Xu, Qiangeng, Chai, Menglei, Prabhu, Anish, Pandey, Rohit, Fanello, Sean, Huang, Zeng, Fu, Yun
Recent works have shown that neural radiance fields (NeRFs) on top of parametric models have reached SOTA quality to build photorealistic head avatars from a monocular video. However, one major limitation of the NeRF-based avatars is the slow renderi
Externí odkaz:
http://arxiv.org/abs/2409.18057
We investigate the localization behavior of two-body Hubbard model in the presence of non-reciprocal tunneling, where the interaction induced Anderson localization competes with the non-Hermitian skin effects and gives rise to diverse patterns of den
Externí odkaz:
http://arxiv.org/abs/2409.07883
Autor:
Zhang, Jianguo, Lan, Tian, Zhu, Ming, Liu, Zuxin, Hoang, Thai, Kokane, Shirley, Yao, Weiran, Tan, Juntao, Prabhakar, Akshara, Chen, Haolin, Liu, Zhiwei, Feng, Yihao, Awalgaonkar, Tulika, Murthy, Rithesh, Hu, Eric, Chen, Zeyuan, Xu, Ran, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing specialized models for agent tasks, driven by the scarcity of high-quality
Externí odkaz:
http://arxiv.org/abs/2409.03215
We theoretically propose that van der Waals monolayer Re(Ag$X_3$)$_2$ ($X=$ Cl, Br, I) have four consecutive flat Chern bands in the 120$^\circ$ spiral antiferromagnetic ground state. The nontrivial topology of these Chern bands emerges from the syne
Externí odkaz:
http://arxiv.org/abs/2409.01741
Autor:
Qin, Can, Xia, Congying, Ramakrishnan, Krithika, Ryoo, Michael, Tu, Lifu, Feng, Yihao, Shu, Manli, Zhou, Honglu, Awadalla, Anas, Wang, Jun, Purushwalkam, Senthil, Xue, Le, Zhou, Yingbo, Wang, Huan, Savarese, Silvio, Niebles, Juan Carlos, Chen, Zeyuan, Xu, Ran, Xiong, Caiming
We present xGen-VideoSyn-1, a text-to-video (T2V) generation model capable of producing realistic scenes from textual descriptions. Building on recent advancements, such as OpenAI's Sora, we explore the latent diffusion model (LDM) architecture and i
Externí odkaz:
http://arxiv.org/abs/2408.12590
Autor:
Xue, Le, Shu, Manli, Awadalla, Anas, Wang, Jun, Yan, An, Purushwalkam, Senthil, Zhou, Honglu, Prabhu, Viraj, Dai, Yutong, Ryoo, Michael S, Kendre, Shrikant, Zhang, Jieyu, Qin, Can, Zhang, Shu, Chen, Chia-Chih, Yu, Ning, Tan, Juntao, Awalgaonkar, Tulika Manoj, Heinecke, Shelby, Wang, Huan, Choi, Yejin, Schmidt, Ludwig, Chen, Zeyuan, Savarese, Silvio, Niebles, Juan Carlos, Xiong, Caiming, Xu, Ran
This report introduces xGen-MM (also known as BLIP-3), a framework for developing Large Multimodal Models (LMMs). The framework comprises meticulously curated datasets, a training recipe, model architectures, and a resulting suite of LMMs. xGen-MM, s
Externí odkaz:
http://arxiv.org/abs/2408.08872
Video Snapshot Compressive Imaging (SCI) uses a low-speed 2D camera to capture high-speed scenes as snapshot compressed measurements, followed by a reconstruction algorithm to retrieve the high-speed video frames. The fast evolving mobile devices and
Externí odkaz:
http://arxiv.org/abs/2408.07530
While randomized trials may be the gold standard for evaluating the effectiveness of the treatment intervention, in some special circumstances, single-arm clinical trials utilizing external control may be considered. The causal treatment effect of in
Externí odkaz:
http://arxiv.org/abs/2408.07193
Autor:
Zhang, Kexun, Yao, Weiran, Liu, Zuxin, Feng, Yihao, Liu, Zhiwei, Murthy, Rithesh, Lan, Tian, Li, Lei, Lou, Renze, Xu, Jiacheng, Pang, Bo, Zhou, Yingbo, Heinecke, Shelby, Savarese, Silvio, Wang, Huan, Xiong, Caiming
Large language model (LLM) agents have shown great potential in solving real-world software engineering (SWE) problems. The most advanced open-source SWE agent can resolve over 27% of real GitHub issues in SWE-Bench Lite. However, these sophisticated
Externí odkaz:
http://arxiv.org/abs/2408.07060
Infrared small target detection faces the inherent challenge of precisely localizing dim targets amidst complex background clutter. Traditional approaches struggle to balance detection precision and false alarm rates. To break this dilemma, we propos
Externí odkaz:
http://arxiv.org/abs/2408.03717