Zobrazeno 1 - 10
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pro vyhledávání: '"Frieder A"'
We study the problem of approximating and estimating classification functions that have their decision boundary in the $RBV^2$ space. Functions of $RBV^2$ type arise naturally as solutions of regularized neural network learning problems and neural ne
Externí odkaz:
http://arxiv.org/abs/2409.17991
Publikováno v:
ACM Symposium on Document Engineering 2024 (DocEng '24), August 20-23, 2024, San Jose, CA, USA. ACM, New York, NY, USA
Sparse retrieval methods like BM25 are based on lexical overlap, focusing on the surface form of the terms that appear in the query and the document. The use of inverted indices in these methods leads to high retrieval efficiency. On the other hand,
Externí odkaz:
http://arxiv.org/abs/2409.05882
Publikováno v:
The Second Workshop on Generative Information Retrieval at ACM SIGIR 2024
Generative language models hallucinate. That is, at times, they generate factually flawed responses. These inaccuracies are particularly insidious because the responses are fluent and well-articulated. We focus on the task of Grounded Answer Generati
Externí odkaz:
http://arxiv.org/abs/2409.00085
Collective light-matter interactions have been used to control chemistry and energy transfer, yet accessible approaches that combine ab initio methodology with large many-body quantum optical systems are missing due to the fast increase in computatio
Externí odkaz:
http://arxiv.org/abs/2408.13570
The manipulation of low-energy matter properties such as superconductivity, ferromagnetism and ferroelectricity via cavity quantum electrodynamics engineering has been suggested as a way to enhance these many-body collective phenomena. In this work,
Externí odkaz:
http://arxiv.org/abs/2407.19478
Autor:
Krause, Stefanie, Stolzenburg, Frieder
Commonsense reasoning is a difficult task for a computer, but a critical skill for an artificial intelligence (AI). It can enhance the explainability of AI models by enabling them to provide intuitive and human-like explanations for their decisions.
Externí odkaz:
http://arxiv.org/abs/2407.03778
Autor:
Pinchetti, Luca, Qi, Chang, Lokshyn, Oleh, Olivers, Gaspard, Emde, Cornelius, Tang, Mufeng, M'Charrak, Amine, Frieder, Simon, Menzat, Bayar, Bogacz, Rafal, Lukasiewicz, Thomas, Salvatori, Tommaso
In this work, we tackle the problems of efficiency and scalability for predictive coding networks in machine learning. To do so, we first propose a library called PCX, whose focus lies on performance and simplicity, and provides a user-friendly, deep
Externí odkaz:
http://arxiv.org/abs/2407.01163
Autor:
Wei, Nathaniel J., Makdah, Adnan El, Hu, JiaCheng, Kaiser, Frieder, Rival, David E., Dabiri, John O.
The unsteady flow physics of wind-turbine wakes under dynamic forcing conditions are critical to the modeling and control of wind farms for optimal power density. Unsteady forcing in the streamwise direction may be generated by unsteady inflow condit
Externí odkaz:
http://arxiv.org/abs/2406.11693
The Kuramoto model and its generalizations have been broadly employed to characterize and mechanistically understand various collective dynamical phenomena, especially the emergence of synchrony among coupled oscillators. Despite almost five decades
Externí odkaz:
http://arxiv.org/abs/2403.02006
Autor:
Chevalier, Alexis, Geng, Jiayi, Wettig, Alexander, Chen, Howard, Mizera, Sebastian, Annala, Toni, Aragon, Max Jameson, Fanlo, Arturo Rodríguez, Frieder, Simon, Machado, Simon, Prabhakar, Akshara, Thieu, Ellie, Wang, Jiachen T., Wang, Zirui, Wu, Xindi, Xia, Mengzhou, Xia, Wenhan, Yu, Jiatong, Zhu, Jun-Jie, Ren, Zhiyong Jason, Arora, Sanjeev, Chen, Danqi
NLP has recently made exciting progress toward training language models (LMs) with strong scientific problem-solving skills. However, model development has not focused on real-life use-cases of LMs for science, including applications in education tha
Externí odkaz:
http://arxiv.org/abs/2402.11111