Zobrazeno 1 - 10
of 795
pro vyhledávání: '"Karlekar, A."'
In this paper, we introduce a novel unbiased regression loss for DETR-based detectors. The conventional $L_{1}$ regression loss tends to bias towards larger boxes, as they disproportionately contribute more towards the overall loss compared to smalle
Externí odkaz:
http://arxiv.org/abs/2410.22638
Autor:
Kagaya, Tomoyuki, Lou, Yuxuan, Yuan, Thong Jing, Lakshmi, Subramanian, Karlekar, Jayashree, Pranata, Sugiri, Murakami, Natsuki, Kinose, Akira, Oguri, Koki, Wick, Felix, You, Yang
In recent years, Large Language Models (LLMs) have demonstrated high reasoning capabilities, drawing attention for their applications as agents in various decision-making processes. One notably promising application of LLM agents is robotic manipulat
Externí odkaz:
http://arxiv.org/abs/2410.16919
Autor:
Jesson, Andrew, Beltran-Velez, Nicolas, Chu, Quentin, Karlekar, Sweta, Kossen, Jannik, Gal, Yarin, Cunningham, John P., Blei, David
This paper presents a method for estimating the hallucination rate for in-context learning (ICL) with generative AI. In ICL, a conditional generative model (CGM) is prompted with a dataset and a prediction question and asked to generate a response. O
Externí odkaz:
http://arxiv.org/abs/2406.07457
Autor:
Kagaya, Tomoyuki, Yuan, Thong Jing, Lou, Yuxuan, Karlekar, Jayashree, Pranata, Sugiri, Kinose, Akira, Oguri, Koki, Wick, Felix, You, Yang
Owing to recent advancements, Large Language Models (LLMs) can now be deployed as agents for increasingly complex decision-making applications in areas including robotics, gaming, and API integration. However, reflecting past experiences in current d
Externí odkaz:
http://arxiv.org/abs/2402.03610
Autor:
Ma, Jiali, Yue, Zhongqi, Tomoyuki, Kagaya, Tomoki, Suzuki, Jayashree, Karlekar, Pranata, Sugiri, Zhang, Hanwang
Fair face recognition is all about learning invariant feature that generalizes to unseen faces in any demographic group. Unfortunately, face datasets inevitably capture the imbalanced demographic attributes that are ubiquitous in real-world observati
Externí odkaz:
http://arxiv.org/abs/2310.14652
Autor:
Rohit Barnabas, Swati Jadhav, Anurag Ranjan Lila, Sirisha Kusuma Boddu, Saba Samad Memon, Sneha Arya, Samiksha Chandrashekhar Hegishte, Manjiri Karlekar, Virendra A Patil, Vijaya Sarathi, Nalini S Shah, Tushar Bandgar
Publikováno v:
Endocrine Connections, Vol 13, Iss 11, Pp 1-11 (2024)
Background: The data on Leydig cell hypoplasia (LCH) resulting from biallelic Luteinizing hormone/chorionic gonadotropin receptor (LHCGR) inactivating variants is limited to case series. Methods: We aim to describe our patients and perform systematic
Externí odkaz:
https://doaj.org/article/0c84a8f16afb46e9a6732b9c23a31184
We are interested in learning robust models from insufficient data, without the need for any externally pre-trained checkpoints. First, compared to sufficient data, we show why insufficient data renders the model more easily biased to the limited tra
Externí odkaz:
http://arxiv.org/abs/2207.12258
Autor:
Manjunath Havalappa Dodamani, Samantha Cheryl Kumar, Samiksha Bhattacharjee, Rohit Barnabas, Sandeep Kumar, Anurag Ranjan Lila, Saba Samad Memon, Manjiri Karlekar, Virendra A. Patil, Tushar R. Bandgar
Publikováno v:
Archives of Endocrinology and Metabolism, Vol 68 (2024)
ABSTRACT Burosumab, a monoclonal antibody directed against the fibroblast growth factor 23 (FGF23), has been approved for the treatment of X-linked hypophosphatemia (XLH). We conducted a systematic review to compare the efficacy and safety of burosum
Externí odkaz:
https://doaj.org/article/95dcdfd6b99d4b2d9388062ccb17aba2
Autor:
Abdullah, Hadi, Karlekar, Aditya, Prasad, Saurabh, Rahman, Muhammad Sajidur, Blue, Logan, Bauer, Luke A., Bindschaedler, Vincent, Traynor, Patrick
Audio CAPTCHAs are supposed to provide a strong defense for online resources; however, advances in speech-to-text mechanisms have rendered these defenses ineffective. Audio CAPTCHAs cannot simply be abandoned, as they are specifically named by the W3
Externí odkaz:
http://arxiv.org/abs/2203.05408
Autor:
Sangeeta Karlekar, Sigamani Jayasingh Albert Chandrasekar, Masilamani Elayaraja, Hemantajit Gogoi, Karuppasamy Govindasamy
Publikováno v:
Фізична реабілітація та рекреаційно-оздоровчі технології, Vol 9, Iss 1, Pp 36-42 (2024)
Purpose: individuals with intellectual disability (ID) often experience challenges related to low levels of physical fitness, impacting both their physical and mental well-being. This study aims to evaluate the pulmonary function of children with ID
Externí odkaz:
https://doaj.org/article/a5e82bb73f564258ba320eb777e9edb6