Zobrazeno 1 - 10
of 29 844
pro vyhledávání: '"Bhatt, A. P."'
Knowledge Graphs (KGs) are essential for the functionality of GraphRAGs, a form of Retrieval-Augmented Generative Systems (RAGs) that excel in tasks requiring structured reasoning and semantic understanding. However, creating KGs for GraphRAGs remain
Externí odkaz:
http://arxiv.org/abs/2412.07412
Autor:
Tripodi, Roberta, Martis, Nicholas, Markov, Vladan, Bradač, Maruša, Di Mascia, Fabio, Cammelli, Vieri, D'Eugenio, Francesco, Willott, Chris, Curti, Mirko, Bhatt, Maulik, Gallerani, Simona, Rihtaršič, Gregor, Singh, Jasbir, Gaspar, Gaia, Harshan, Anishya, Judež, Jon, Merida, Rosa M., Desprez, Guillaume, Sawicki, Marcin, Goovaerts, Ilias, Muzzin, Adam, Noirot, Gaël, Sarrouh, Ghassan T. E., Abraham, Roberto, Asada, Yoshihisa, Brammer, Gabriel, Carpenter, Vicente Estrada, Felicioni, Giordano, Fujimoto, Seiji, Iyer, Kartheik, Mowla, Lamiya, Strait, Victoria
The James Webb Space Telescope (JWST) has recently discovered a new population of objects at high redshift referred to as `Little Red Dots' (LRDs). Their nature currently remains elusive, despite their surprisingly high inferred number densities. Thi
Externí odkaz:
http://arxiv.org/abs/2412.04983
Autor:
Wen, Jiaxin, Hebbar, Vivek, Larson, Caleb, Bhatt, Aryan, Radhakrishnan, Ansh, Sharma, Mrinank, Sleight, Henry, Feng, Shi, He, He, Perez, Ethan, Shlegeris, Buck, Khan, Akbir
As large language models (LLMs) become increasingly capable, it is prudent to assess whether safety measures remain effective even if LLMs intentionally try to bypass them. Previous work introduced control evaluations, an adversarial framework for te
Externí odkaz:
http://arxiv.org/abs/2411.17693
Autor:
Shandilya, Anurag, Bhat, Swapnil, Gautam, Akshat, Yadav, Subhash, Bhatt, Siddharth, Mehta, Deval, Jadhav, Kshitij
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-tailed dataset augmentation, and scaling machine learning algorithms. Fo
Externí odkaz:
http://arxiv.org/abs/2411.17535
Autor:
Chakradeo, Kaustubh, Nielsen, Pernille, Gjerdrum, Lise Mette Rahbek, Hansen, Gry Sahl, Duchêne, David A, Mortensen, Laust H, Jensen, Majken K, Bhatt, Samir
As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age. Identifying biomarkers that distinguish fast from slow ageing is crucial for understanding th
Externí odkaz:
http://arxiv.org/abs/2411.16956
Autor:
Chapai, Ramakanta, Koshelev, Alexei E., Smylie, Matthew P., Chung, Duck Young, Kayani, Asghar, Bhatt, Khushi, Rimal, Gaurab, Kanatzidis, Mercouri G., Kwok, Wai-Kwong, Mitchell, John, Welp, Ulrich
Van Hove singularities (vHs) located close to the Fermi level in Kagome superconductors AV3Sb5 (A = K, Rb, Cs) have profound influence on their electronic and transport characteristics. Specifically, magneto-transport and susceptibility measurements
Externí odkaz:
http://arxiv.org/abs/2411.16625
Autor:
Bhatt, Ahan, Vaghela, Nandan
This paper introduces Med-Bot, an AI-powered chatbot designed to provide users with accurate and reliable medical information. Utilizing advanced libraries and frameworks such as PyTorch, Chromadb, Langchain and Autogptq, Med-Bot is built to handle t
Externí odkaz:
http://arxiv.org/abs/2411.09648
Autor:
Chaudhary, Muhammad F. A., Aguilera, Stephanie M., Nakhmani, Arie, Reinhardt, Joseph M., Bhatt, Surya P., Bodduluri, Sandeep
Diffeomorphic deformable image registration ensures smooth invertible transformations across inspiratory and expiratory chest CT scans. Yet, in practice, deep learning-based diffeomorphic methods struggle to capture large deformations between inspira
Externí odkaz:
http://arxiv.org/abs/2411.07567
Satellite clock bias prediction plays a crucial role in enhancing the accuracy of satellite navigation systems. In this paper, we propose an approach utilizing Long Short-Term Memory (LSTM) networks to predict satellite clock bias. We gather data fro
Externí odkaz:
http://arxiv.org/abs/2411.07015
Autor:
Sharma, Anantha, John, Sheeba Elizabeth, Nikroo, Fatemeh Rezapoor, Bhatt, Krupali, Zambre, Mrunal, Wikhe, Aditi
The growth of digital documents presents significant challenges in efficient management and knowledge extraction. Traditional methods often struggle with complex documents, leading to issues such as hallucinations and high latency in responses from L
Externí odkaz:
http://arxiv.org/abs/2411.05936