Zobrazeno 1 - 10
of 428 509
pro vyhledávání: '"Reddy As"'
Omnichain Web: The Universal Framework for Streamlined Chain Abstraction and Cross-Layer Interaction
The evolution of the Web3 ecosystem has been hindered by fragmented liquidity and limited interoperability across Layer 1 (L1) and Layer 2 (L2) blockchains, which leads to inefficiencies and elevated costs. Omnichain Web addresses these challenges by
Externí odkaz:
http://arxiv.org/abs/2411.10132
Reproducibility in scientific research, particularly within the realm of natural language processing (NLP), is essential for validating and verifying the robustness of experimental findings. This paper delves into the reproduction and evaluation of d
Externí odkaz:
http://arxiv.org/abs/2410.15962
The difficulties of underwater image degradation due to light scattering, absorption, and fog-like particles which lead to low resolution and poor visibility are discussed in this study report. We suggest a sophisticated hybrid strategy that combines
Externí odkaz:
http://arxiv.org/abs/2410.14285
Autor:
Chakraborty, Novoneel, Tandon, Anshoo, Reddy, Kailash, Kirpekar, Kaushal, Robert, Bryan Paul, Kumar, Hari Dilip, Venkatesh, Abhilash, Sharma, Abhay
Data de-identification makes it possible to glean insights from data while preserving user privacy. The use of Trusted Execution Environments (TEEs) allow for the execution of de-identification applications on the cloud without the need for a user to
Externí odkaz:
http://arxiv.org/abs/2412.09222
Autor:
Sethi, Sahil, Reddy, Sai, Sakarvadia, Mansi, Serotte, Jordan, Nwaudo, Darlington, Maassen, Nicholas, Shi, Lewis
Bankart lesions, or anterior-inferior glenoid labral tears, are diagnostically challenging on standard MRIs due to their subtle imaging features-often necessitating invasive MRI arthrograms (MRAs). This study develops deep learning (DL) models to det
Externí odkaz:
http://arxiv.org/abs/2412.06717
Autor:
Alam, Nahid, Kanjula, Karthik Reddy, Guthikonda, Surya, Chung, Timothy, Vegesna, Bala Krishna S, Das, Abhipsha, Susevski, Anthony, Chan, Ryan Sze-Yin, Uddin, S M Iftekhar, Islam, Shayekh Bin, Santhosh, Roshan, A, Snegha, Sharma, Drishti, Liu, Chen, Chaturvedi, Isha, Winata, Genta Indra, S, Ashvanth., Mukherjee, Snehanshu, Aji, Alham Fikri
The rapid development of large Vision-Language Models (VLMs) has led to impressive results on academic benchmarks, primarily in widely spoken languages. However, significant gaps remain in the ability of current VLMs to handle low-resource languages
Externí odkaz:
http://arxiv.org/abs/2412.07112
Proper use of personal protective equipment (PPE) can save the lives of industry workers and it is a widely used application of computer vision in the large manufacturing industries. However, most of the applications deployed generate a lot of false
Externí odkaz:
http://arxiv.org/abs/2412.05531
Autor:
De Chezelles, Thibault Le Sellier, Gasse, Maxime, Drouin, Alexandre, Caccia, Massimo, Boisvert, Léo, Thakkar, Megh, Marty, Tom, Assouel, Rim, Shayegan, Sahar Omidi, Jang, Lawrence Keunho, Lù, Xing Han, Yoran, Ori, Kong, Dehan, Xu, Frank F., Reddy, Siva, Cappart, Quentin, Neubig, Graham, Salakhutdinov, Ruslan, Chapados, Nicolas, Lacoste, Alexandre
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those leveraging automation and Large Language Models (LLMs) for web interaction tasks. Many existing benchmarks suffer from fra
Externí odkaz:
http://arxiv.org/abs/2412.05467
Autor:
Magnani, Alessandro, Liu, Feng, Chaidaroon, Suthee, Yadav, Sachin, Suram, Praveen Reddy, Puthenputhussery, Ajit, Chen, Sijie, Xie, Min, Kashi, Anirudh, Lee, Tony, Liao, Ciya
In product search, the retrieval of candidate products before re-ranking is more critical and challenging than other search like web search, especially for tail queries, which have a complex and specific search intent. In this paper, we present a hyb
Externí odkaz:
http://arxiv.org/abs/2412.04637
Autor:
Rodriguez, Juan, Jian, Xiangru, Panigrahi, Siba Smarak, Zhang, Tianyu, Feizi, Aarash, Puri, Abhay, Kalkunte, Akshay, Savard, François, Masry, Ahmed, Nayak, Shravan, Awal, Rabiul, Massoud, Mahsa, Abaskohi, Amirhossein, Li, Zichao, Wang, Suyuchen, Noël, Pierre-André, Richter, Mats Leon, Vadacchino, Saverio, Agarwal, Shubbam, Biswas, Sanket, Shanian, Sara, Zhang, Ying, Bolger, Noah, MacDonald, Kurt, Fauvel, Simon, Tejaswi, Sathwik, Sunkara, Srinivas, Monteiro, Joao, Dvijotham, Krishnamurthy DJ, Scholak, Torsten, Chapados, Nicolas, Kharagani, Sepideh, Hughes, Sean, Özsu, M., Reddy, Siva, Pedersoli, Marco, Bengio, Yoshua, Pal, Christopher, Laradji, Issam, Gella, Spandanna, Taslakian, Perouz, Vazquez, David, Rajeswar, Sai
Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and summarizing reports. Code generation tasks that require long-structured o
Externí odkaz:
http://arxiv.org/abs/2412.04626