Zobrazeno 1 - 10
of 596 374
pro vyhledávání: '"A. Woo"'
Continual Imitation Learning (CiL) involves extracting and accumulating task knowledge from demonstrations across multiple stages and tasks to achieve a multi-task policy. With recent advancements in foundation models, there has been a growing intere
Externí odkaz:
http://arxiv.org/abs/2410.22658
Autor:
Woo, Soojin, Kim, Seong-Woo
In vision-based robot localization and SLAM, Visual Place Recognition (VPR) is essential. This paper addresses the problem of VPR, which involves accurately recognizing the location corresponding to a given query image. A popular approach to vision-b
Externí odkaz:
http://arxiv.org/abs/2410.19341
Transporting between arbitrary distributions is a fundamental goal in generative modeling. Recently proposed diffusion bridge models provide a potential solution, but they rely on a joint distribution that is difficult to obtain in practice. Furtherm
Externí odkaz:
http://arxiv.org/abs/2410.01500
Autor:
Kim, Chan, Kim, Keonwoo, Oh, Mintaek, Baek, Hanbi, Lee, Jiyang, Jung, Donghwi, Woo, Soojin, Woo, Younkyung, Tucker, John, Firoozi, Roya, Seo, Seung-Woo, Schwager, Mac, Kim, Seong-Woo
Large language models (LLMs) have shown significant potential in guiding embodied agents to execute language instructions across a range of tasks, including robotic manipulation and navigation. However, existing methods are primarily designed for sta
Externí odkaz:
http://arxiv.org/abs/2409.10027
Autor:
Cho, Woojin, Lee, Jihyun, Yi, Minjae, Kim, Minje, Woo, Taeyun, Kim, Donghwan, Ha, Taewook, Lee, Hyokeun, Ryu, Je-Hwan, Woo, Woontack, Kim, Tae-Kyun
Existing datasets for 3D hand-object interaction are limited either in the data cardinality, data variations in interaction scenarios, or the quality of annotations. In this work, we present a comprehensive new training dataset for hand-object intera
Externí odkaz:
http://arxiv.org/abs/2409.04033
Extraction of hot carriers (HCs) over the band-edge is a key to harvest solar energy beyond Shockley-Queisser limit1. Graphene is known as a HC-layered material due to phonon bottleneck effect near Dirac point, but limited by low photocarrier density
Externí odkaz:
http://arxiv.org/abs/2411.05727
Autor:
Kavuri, Gautam A., Palfree, Jasper, Reddy, Dileep V., Zhang, Yanbao, Bienfang, Joshua C., Mazurek, Michael D., Alhejji, Mohammad A., Siddiqui, Aliza U., Cavanagh, Joseph M., Dalal, Aagam, Abellán, Carlos, Amaya, Waldimar, Mitchell, Morgan W., Stange, Katherine E., Beale, Paul D., Brandão, Luís T. A. N., Booth, Harold, Peralta, René, Nam, Sae Woo, Mirin, Richard P., Stevens, Martin J., Knill, Emanuel, Shalm, Lynden K.
The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations-the generation processes cannot be fully traced, audited, an
Externí odkaz:
http://arxiv.org/abs/2411.05247
Anomalous transverse transport of electrons such as the anomalous Hall effect and the anomalous Nernst effect provide opportunities to realize advanced spintronic and thermoelectric devices. To materialize these opportunities, it is crucial to streng
Externí odkaz:
http://arxiv.org/abs/2411.04433
We study the instability of antiferromagnets with easy-axis anisotropy under a magnetic field, uncovering single or even multiple phase transitions at the boundary between non-collinear and collinear spin orderings. Near the phase boundary, the entan
Externí odkaz:
http://arxiv.org/abs/2411.02338
Autor:
Li, Wen-Ding, Hu, Keya, Larsen, Carter, Wu, Yuqing, Alford, Simon, Woo, Caleb, Dunn, Spencer M., Tang, Hao, Naim, Michelangelo, Nguyen, Dat, Zheng, Wei-Long, Tavares, Zenna, Pu, Yewen, Ellis, Kevin
When learning an input-output mapping from very few examples, is it better to first infer a latent function that explains the examples, or is it better to directly predict new test outputs, e.g. using a neural network? We study this question on ARC,
Externí odkaz:
http://arxiv.org/abs/2411.02272