Zobrazeno 1 - 10
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pro vyhledávání: '"A, Orhan"'
Recent advances in Large Language Models (LLMs) have positively and efficiently transformed workflows in many domains. One such domain with significant potential for LLM integration is the Internet of Things (IoT), where this integration brings new o
Externí odkaz:
http://arxiv.org/abs/2411.17722
Autor:
Prete, Andrea Dal, Orhan, Zeynep Özge, Bolotnikova, Anastasia, Gandolla, Marta, Ijspeert, Auke, Bouri, Mohamed
Accurate detection of locomotion transitions, such as walk to sit, walk to stair ascent, and descent, is crucial to effectively control robotic assistive devices, such as lower-limb exoskeletons, as each locomotion mode requires specific assistance.
Externí odkaz:
http://arxiv.org/abs/2411.12573
We evaluate the reliability of two chatbots, ChatGPT (4o and o1-preview versions), and Gemini Advanced, in providing references on financial literature and employing novel methodologies. Alongside the conventional binary approach commonly used in the
Externí odkaz:
http://arxiv.org/abs/2411.07031
Autor:
Vodrahalli, Kiran, Ontanon, Santiago, Tripuraneni, Nilesh, Xu, Kelvin, Jain, Sanil, Shivanna, Rakesh, Hui, Jeffrey, Dikkala, Nishanth, Kazemi, Mehran, Fatemi, Bahare, Anil, Rohan, Dyer, Ethan, Shakeri, Siamak, Vij, Roopali, Mehta, Harsh, Ramasesh, Vinay, Le, Quoc, Chi, Ed, Lu, Yifeng, Firat, Orhan, Lazaridou, Angeliki, Lespiau, Jean-Baptiste, Attaluri, Nithya, Olszewska, Kate
We introduce Michelangelo: a minimal, synthetic, and unleaked long-context reasoning evaluation for large language models which is also easy to automatically score. This evaluation is derived via a novel, unifying framework for evaluations over arbit
Externí odkaz:
http://arxiv.org/abs/2409.12640
Autor:
Orhan, Okan K., Bello, Frank Daniel, Abadía, Nicolás, Hess, Ortwin, Donegan, John F., O'Regan, David D.
Plasmonic near-field transducers (NFTs) play a key role in administering nanoscale heating for a number of applications ranging from medical devices to next generation data processing technology. We present a novel multi-scale approach, combining qua
Externí odkaz:
http://arxiv.org/abs/2408.14451
High-entropy alloys (HEAs) exhibit exceptional catalytic performance due to their complex surface structures. However, the vast number of active binding sites in HEAs, as opposed to conventional alloys, presents a significant computational challenge
Externí odkaz:
http://arxiv.org/abs/2408.11238
Autor:
Donmez, Orhan
Research on the Horndeski black hole, associated with the scalar hairy parameter, offers insights into enigmatic cosmic phenomena such as dark matter. Additionally, the numerical study of the GRS 1915+105 source, which exhibits continuous variability
Externí odkaz:
http://arxiv.org/abs/2408.10102
Autor:
Errehymy, Abdelghani, Khedif, Youssef, Donmez, Orhan, Daoud, Mohammed, Myrzakulov, Kairat, Bekov, Sabit
In this paper, we present new generalized wormhole (WH) solutions within the context of $f(R)$ gravity. Specifically, we focus on $f(R)$ gravitational theories formulated in the metric formalism, with our investigation centered on a power-law form re
Externí odkaz:
http://arxiv.org/abs/2408.07667
In this paper, we address the optimal sampling of a Wiener process under sampling and transmission costs, with the samples being forwarded to a remote estimator over a channel with random IID delay. The goal of the estimator is to reconstruct an esti
Externí odkaz:
http://arxiv.org/abs/2407.21181
Autor:
Orhan, A. Emin
We introduce Human-like Video Models (HVM-1), large-scale video models pretrained with nearly 5000 hours of curated human-like video data (mostly egocentric, temporally extended, continuous video recordings), using the spatiotemporal masked autoencod
Externí odkaz:
http://arxiv.org/abs/2407.18067