Zobrazeno 1 - 10
of 989
pro vyhledávání: '"Le, Tuan Anh"'
In future wireless systems of beyond 5G and 6G, addressing diverse applications with varying quality requirements is essential. Open Radio Access Network (O-RAN) architectures offer the potential for dynamic resource adaptation based on traffic deman
Externí odkaz:
http://arxiv.org/abs/2410.02954
The differences in H2O2 production between conventional (CONV) and ultra-high dose rate (UHDR) irradiations in water radiolysis are still not fully understood. The lower levels of this radiolytic species, as a critical end product of water radiolysis
Externí odkaz:
http://arxiv.org/abs/2409.11993
In developing medical interventions using untethered milli- and microrobots, ensuring safety and effectiveness relies on robust methods for detection, real-time tracking, and precise localization within the body. However, the inherent non-transparenc
Externí odkaz:
http://arxiv.org/abs/2409.08337
Autor:
Hoang, Manh Kha, Le, Tuan Anh, Thuc, Kieu-Xuan, Van Luyen, Tong, Yang, Xin-She, Ng, Derrick Wing Kwan
This letter addresses a multivariate optimization problem for linear movable antenna arrays (MAAs). Particularly, the position and beamforming vectors of the under-investigated MAA are optimized simultaneously to maximize the minimum beamforming gain
Externí odkaz:
http://arxiv.org/abs/2409.04228
As the role of knowledge-based systems in IoT keeps growing, ensuring resource efficiency of RDF stores becomes critical. However, up until now benchmarks of RDF stores were most often conducted with only one dataset, and the differences between the
Externí odkaz:
http://arxiv.org/abs/2406.16412
Autor:
Kästner, Linh, Shcherbyna, Volodymyir, Zeng, Huajian, Le, Tuan Anh, Schreff, Maximilian Ho-Kyoung, Osmaev, Halid, Tran, Nam Truong, Diaz, Diego, Golebiowski, Jan, Soh, Harold, Lambrecht, Jens
Publikováno v:
Robotics Science and Systems 2024, Delft Netherlands
Building upon our previous contributions, this paper introduces Arena 3.0, an extension of Arena-Bench, Arena 1.0, and Arena 2.0. Arena 3.0 is a comprehensive software stack containing multiple modules and simulation environments focusing on the deve
Externí odkaz:
http://arxiv.org/abs/2406.00837
Unsupervised Domain Adaptation (UDA) has shown significant advancements in object detection under well-lit conditions; however, its performance degrades notably in low-visibility scenarios, especially at night, posing challenges not only for its adap
Externí odkaz:
http://arxiv.org/abs/2404.01988
We give a model of how to infer natural language rules by doing experiments. The model integrates Large Language Models (LLMs) with Monte Carlo algorithms for probabilistic inference, interleaving online belief updates with experiment design under in
Externí odkaz:
http://arxiv.org/abs/2402.06025
How do we infer a 3D scene from a single image in the presence of corruptions like rain, snow or fog? Straightforward domain randomization relies on knowing the family of corruptions ahead of time. Here, we propose a Bayesian approach-dubbed robust i
Externí odkaz:
http://arxiv.org/abs/2402.01915
Autor:
Phan, Du, Hoffman, Matthew D., Dohan, David, Douglas, Sholto, Le, Tuan Anh, Parisi, Aaron, Sountsov, Pavel, Sutton, Charles, Vikram, Sharad, Saurous, Rif A.
Large language models (LLMs) solve problems more accurately and interpretably when instructed to work out the answer step by step using a ``chain-of-thought'' (CoT) prompt. One can also improve LLMs' performance on a specific task by supervised fine-
Externí odkaz:
http://arxiv.org/abs/2312.02179