Zobrazeno 1 - 10
of 14 106
pro vyhledávání: '"SRIDEVI, A."'
Autor:
Kuriyattil, Sridevi, Poggi, Pablo M., Pritchard, Jonathan D., Kombe, Johannes, Daley, Andrew J.
Quantum states featuring extensive multipartite entanglement are a resource for quantum-enhanced metrology, with sensitivity up to the Heisenberg limit. However, robust generation of these states using unitary dynamics typically requires all-to-all i
Externí odkaz:
http://arxiv.org/abs/2412.10010
Autor:
Tedeschi, Mary C., Ricaurte, Paola, Ayloo, Sridevi, Corneli, Joseph, Danoff, Charles Jeffrey, Belich, Sergio
At EuroPLoP 2024 Mary Tedeschi led the "AI Future Envisioning with PLACARD" focus group in Germany. Three conference attendees joined in the room while Sridevi, Paola, and Charles co-facilitated remotely via a web conference. The participants were in
Externí odkaz:
http://arxiv.org/abs/2410.17155
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
Autor:
Sinthuja, U, Sridevi, R
This work proposes a tool to estimate the interference between nodes and links in a live wireless network by passive monitoring of wireless traffic. This approach requires deploying multiple sniffers across the network to capture wireless traffic tra
Externí odkaz:
http://arxiv.org/abs/2407.10997
Autor:
Sridevi, R., Shobana, P.
Publikováno v:
Aegaeum Journal Volume 8 Issue 10 (2020) 402-410
The standard methods of identification such as PIN Numbers (Personal Identification Number), Passwords, smart cards can be easily stolen and can be misused easily. To overcome this, biometric is introduced, as it will be unique to each individual. In
Externí odkaz:
http://arxiv.org/abs/2406.11335
Essential tasks in autonomous driving includes environment perception, detection and tracking, path planning and action control. This paper focus on path planning, which is one of the challenging task as it needs to find optimal path in highly comple
Externí odkaz:
http://arxiv.org/abs/2402.12129
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
Large language models (LLMs) have shown remarkable achievements in natural language processing tasks, producing high-quality outputs. However, LLMs still exhibit limitations, including the generation of factually incorrect information. In safety-crit
Externí odkaz:
http://arxiv.org/abs/2311.09358
Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations. Retrieval-augmented LLMs provide a non-parametric approach to solve thes
Externí odkaz:
http://arxiv.org/abs/2311.04348
Autor:
Acharya, Anurag, Munikoti, Sai, Hellinger, Aaron, Smith, Sara, Wagle, Sridevi, Horawalavithana, Sameera
As LLMs have become increasingly popular, they have been used in almost every field. But as the application for LLMs expands from generic fields to narrow, focused science domains, there exists an ever-increasing gap in ways to evaluate their efficac
Externí odkaz:
http://arxiv.org/abs/2310.10920