Zobrazeno 1 - 10
of 7 159
pro vyhledávání: '"Wagle A"'
Autor:
Bonatti, Rogerio, Zhao, Dan, Bonacci, Francesco, Dupont, Dillon, Abdali, Sara, Li, Yinheng, Lu, Yadong, Wagle, Justin, Koishida, Kazuhito, Bucker, Arthur, Jang, Lawrence, Hui, Zack
Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning and reasoning. However, measuring agent performance in realistic envi
Externí odkaz:
http://arxiv.org/abs/2409.08264
Autor:
Meyur, Rounak, Phan, Hung, Wagle, Sridevi, Strube, Jan, Halappanavar, Mahantesh, Horawalavithana, Sameera, Acharya, Anurag, Munikoti, Sai
In the rapidly evolving landscape of Natural Language Processing (NLP) and text generation, the emergence of Retrieval Augmented Generation (RAG) presents a promising avenue for improving the quality and reliability of generated text by leveraging in
Externí odkaz:
http://arxiv.org/abs/2408.11800
Using Large Language Models (LLMs) to generate synthetic data for model training has become increasingly popular in recent years. While LLMs are capable of producing realistic training data, the effectiveness of data generation is influenced by vario
Externí odkaz:
http://arxiv.org/abs/2407.12813
Autor:
Wagle, Dinesh, Stoeffler, Daniel, Temdie, Loic, Kaffash, Mojtaba Taghipour, Castel, Vincent, Majjad, H., Bernard, R., Henry, Yves, Bailleul, Matthieu, Jungfleisch, M. Benjamin, Vlaminck, Vincent
A caustic is a mathematical concept describing the beam formation when the beam envelope is reflected or refracted by a manifold. While caustics are common in a wide range of physical systems, caustics typically exhibit a reciprocal wave propagation
Externí odkaz:
http://arxiv.org/abs/2404.15011
Federated learning (FL) is a popular solution for distributed machine learning (ML). While FL has traditionally been studied for supervised ML tasks, in many applications, it is impractical to assume availability of labeled data across devices. To th
Externí odkaz:
http://arxiv.org/abs/2404.09861
Through a large-scale study over diverse face images, we show that facial attribute editing using modern generative AI models can severely degrade automated face recognition systems. This degradation persists even with identity-preserving generative
Externí odkaz:
http://arxiv.org/abs/2403.08092
One of the main challenges of decentralized machine learning paradigms such as Federated Learning (FL) is the presence of local non-i.i.d. datasets. Device-to-device transfers (D2D) between distributed devices has been shown to be an effective tool f
Externí odkaz:
http://arxiv.org/abs/2402.09629
Publikováno v:
J. Phys. Mater. 7, 025005 (2024)
The tunability of magnons enables their interaction with various other quantum excitations, including photons, paving the route for novel hybrid quantum systems. Here, we study magnon-photon coupling using a high-quality factor split-ring resonator a
Externí odkaz:
http://arxiv.org/abs/2402.03071
Publikováno v:
Phys. Rev. D 109, 044072 (2024)
We present a novel approach, $\textit{Metric pErTuRbations wIth speCtral methodS}$ (METRICS), to calculate the gravitational metric perturbations and the quasinormal-mode frequencies of rotating black holes of any spin without decoupling the lineariz
Externí odkaz:
http://arxiv.org/abs/2312.08435
Large language models record impressive performance on many natural language processing tasks. However, their knowledge capacity is limited to the pretraining corpus. Retrieval augmentation offers an effective solution by retrieving context from exte
Externí odkaz:
http://arxiv.org/abs/2311.12289