Zobrazeno 1 - 10
of 11 747
pro vyhledávání: '"Meghana A."'
Autor:
Caralt, Mireia Hernandez, Sekulić, Ivan, Carević, Filip, Khau, Nghia, Popa, Diana Nicoleta, Guedes, Bruna, Guimarães, Victor, Yang, Zeyu, Manso, Andre, Reddy, Meghana, Rosso, Paolo, Mathis, Roland
Detecting user frustration in modern-day task-oriented dialog (TOD) systems is imperative for maintaining overall user satisfaction, engagement, and retention. However, most recent research is focused on sentiment and emotion detection in academic se
Externí odkaz:
http://arxiv.org/abs/2411.17437
We consider the Hospital/Residents (HR) problem in the presence of ties in preference lists. Among the three notions of stability, viz. weak, strong, and super stability, we focus on the notion of strong stability. Strong stability has many desirable
Externí odkaz:
http://arxiv.org/abs/2411.10284
Autor:
Ramamurthy, Rajkumar, Rajeev, Meghana Arakkal, Molenschot, Oliver, Zou, James, Rajani, Nazneen
Large language models (LLMs) often fail to synthesize information from their context to generate an accurate response. This renders them unreliable in knowledge intensive settings where reliability of the output is key. A critical component for relia
Externí odkaz:
http://arxiv.org/abs/2411.03300
Autor:
Trivedi, Prapti, Gulati, Aditya, Molenschot, Oliver, Rajeev, Meghana Arakkal, Ramamurthy, Rajkumar, Stevens, Keith, Chaudhery, Tanveesh Singh, Jambholkar, Jahnavi, Zou, James, Rajani, Nazneen
LLM-as-a-judge models have been used for evaluating both human and AI generated content, specifically by providing scores and rationales. Rationales, in addition to increasing transparency, help models learn to calibrate its judgments. Enhancing a mo
Externí odkaz:
http://arxiv.org/abs/2410.05495
Autor:
Ruihan Yang, Yina Ma, Bao-Bao Pan, Meghana A. Bhatt, Terry Lohrenz, Hua-Guang Gu, Jonathan W. Kanen, Colin F. Camerer, P. Read Montague, Qiang Luo
Publikováno v:
NeuroImage, Vol 263, Iss , Pp 119585- (2022)
Information exchange between brain regions is key to understanding information processing for social decision-making, but most analyses ignore its dynamic nature. New insights on this dynamic might help us to uncover the neural correlates of social c
Externí odkaz:
https://doaj.org/article/ad2ea8ce80a8445cb37b535739061c4c
Increased healthcare demand is significantly straining European services. Digital solutions including advanced modelling techniques offer a promising solution to optimising patient flow without impacting day-to-day healthcare provision. In this work
Externí odkaz:
http://arxiv.org/abs/2410.12804
Autor:
Kumar, Avisha, Kotkar, Kunal, Jiang, Kelly, Bhimreddy, Meghana, Davidar, Daniel, Weber-Levine, Carly, Krishnan, Siddharth, Kerensky, Max J., Liang, Ruixing, Leadingham, Kelley Kempski, Routkevitch, Denis, Hersh, Andrew M., Ashayeri, Kimberly, Tyler, Betty, Suk, Ian, Son, Jennifer, Theodore, Nicholas, Thakor, Nitish, Manbachi, Amir
While deep learning has catalyzed breakthroughs across numerous domains, its broader adoption in clinical settings is inhibited by the costly and time-intensive nature of data acquisition and annotation. To further facilitate medical machine learning
Externí odkaz:
http://arxiv.org/abs/2409.16441
Autor:
Chakravarthy, Anirudh S, Ganesina, Meghana Reddy, Hu, Peiyun, Leal-Taixe, Laura, Kong, Shu, Ramanan, Deva, Osep, Aljosa
Addressing Lidar Panoptic Segmentation (LPS ) is crucial for safe deployment of autonomous vehicles. LPS aims to recognize and segment lidar points w.r.t. a pre-defined vocabulary of semantic classes, including thing classes of countable objects (e.g
Externí odkaz:
http://arxiv.org/abs/2409.14273
Autor:
Li, Juno, Da Cunha, Elisabete, González-López, Jorge, Aravena, Manuel, De Looze, Ilse, Schreiber, N. M. Förster, Herrera-Camus, Rodrigo, Spilker, Justin, Tadaki, Ken-ichi, Barcos-Munoz, Loreto, Battisti, Andrew J., Birkin, Jack E., Bowler, Rebecca A. A., Davies, Rebecca, Díaz-Santos, Tanio, Ferrara, Andrea, Fisher, Deanne B., Hodge, Jacqueline, Ikeda, Ryota, Killi, Meghana, Lee, Lilian, Liu, Daizhong, Lutz, Dieter, Mitsuhashi, Ikki, Naab, Thorsten, Posses, Ana, Relaño, Monica, Solimano, Manuel, Übler, Hannah, van der Giessen, Stefan Anthony, Villanueva, Vicente
Using a combination of HST, JWST, and ALMA data, we perform spatially resolved spectral energy distributions (SED) fitting of fourteen 4
Externí odkaz:
http://arxiv.org/abs/2409.10961
Autor:
Biswas, Koushik, Pal, Ridal, Patel, Shaswat, Jha, Debesh, Karri, Meghana, Reza, Amit, Durak, Gorkem, Medetalibeyoglu, Alpay, Antalek, Matthew, Velichko, Yury, Ladner, Daniela, Borhani, Amir, Bagci, Ulas
Accurately segmenting different organs from medical images is a critical prerequisite for computer-assisted diagnosis and intervention planning. This study proposes a deep learning-based approach for segmenting various organs from CT and MRI scans an
Externí odkaz:
http://arxiv.org/abs/2408.05692