Zobrazeno 1 - 10
of 16 863
pro vyhledávání: '"A Néel"'
Autor:
Moayeri, Mazda, Balachandran, Vidhisha, Chandrasekaran, Varun, Yousefi, Safoora, Fel, Thomas, Feizi, Soheil, Nushi, Besmira, Joshi, Neel, Vineet, Vibhav
With models getting stronger, evaluations have grown more complex, testing multiple skills in one benchmark and even in the same instance at once. However, skill-wise performance is obscured when inspecting aggregate accuracy, under-utilizing the ric
Externí odkaz:
http://arxiv.org/abs/2410.13826
Single metallocene molecules act as sensitive spin detectors when decorating the probe of a scanning tunneling microscope (STM). However, the impact of the atomic-scale electrode details on the molecular spin state has remained elusive to date. Here,
Externí odkaz:
http://arxiv.org/abs/2410.07777
This paper proposes a hybrid quantum neural network (HQNN) for indoor user localization using received signal strength indicator (RSSI) values. We use publicly available RSSI datasets for indoor localization using WiFi, Bluetooth, and Zigbee to test
Externí odkaz:
http://arxiv.org/abs/2410.00708
Recent advancements in Large Language Models (LLMs) have showcased their ability to perform complex reasoning tasks, but their effectiveness in planning remains underexplored. In this study, we evaluate the planning capabilities of OpenAI's o1 models
Externí odkaz:
http://arxiv.org/abs/2409.19924
Autor:
Kouroudis, Ioannis, Poonam, Misciaci, Neel, Mayr, Felix, Müller, Leon, Gu, Zhaosu, Gagliardi, Alessio
In this paper, we propose a novel flexible optimization pipeline for determining the optimal adsorption sites, named AUGUR (Aware of Uncertainty Graph Unit Regression). Our model combines graph neural networks and Gaussian processes to create a flexi
Externí odkaz:
http://arxiv.org/abs/2409.16204
Autor:
Saad-Falcon, Jon, Lafuente, Adrian Gamarra, Natarajan, Shlok, Maru, Nahum, Todorov, Hristo, Guha, Etash, Buchanan, E. Kelly, Chen, Mayee, Guha, Neel, Ré, Christopher, Mirhoseini, Azalia
Inference-time techniques are emerging as highly effective tools to enhance large language model (LLM) capabilities. However, best practices for developing systems that combine these techniques remain underdeveloped due to our limited understanding o
Externí odkaz:
http://arxiv.org/abs/2409.15254
Due to the numerous limitations of current quantum devices, quantum error mitigation methods become potential solutions for realizing practical quantum applications in the near term. Zero-Noise Extrapolation (ZNE) and Clifford Data Regression (CDR) a
Externí odkaz:
http://arxiv.org/abs/2409.14632
Although powerful, current cutting-edge LLMs may not fulfil the needs of highly specialised sectors. We introduce KodeXv0.1, a family of large language models that outclass GPT-4 in financial question answering. We utilise the base variants of Llama
Externí odkaz:
http://arxiv.org/abs/2409.13749
Autor:
Balachandran, Vidhisha, Chen, Jingya, Joshi, Neel, Nushi, Besmira, Palangi, Hamid, Salinas, Eduardo, Vineet, Vibhav, Woffinden-Luey, James, Yousefi, Safoora
Rigorous and reproducible evaluation is critical for assessing the state of the art and for guiding scientific advances in Artificial Intelligence. Evaluation is challenging in practice due to several reasons, including benchmark saturation, lack of
Externí odkaz:
http://arxiv.org/abs/2409.10566
Autor:
Johnson, Timothy, Sutcliffe, Graeme, Pearcy, Jacob, Birkel, Andrew, Rigon, Gabriel, Kabadi, Neel, Lahmann, Brandon, Adrian, Patrick, Reichelt, Benjamin, Kunimune, Justin, Dannhoff, Skylar, Cufari, Matt, Tsung, Frank, Chen, Hui, Katz, Joseph, Tikhonchuk, Vladimir, Li, Chikang
This letter reports the first complete observation of magnetized collisionless shock precursors formed through the compression of Biermann-battery magnetic fields in laser produced plasmas. At OMEGA, lasers produce a supersonic CH plasma flow which i
Externí odkaz:
http://arxiv.org/abs/2409.03076