Zobrazeno 1 - 10
of 23 650
pro vyhledávání: '"A. Askari"'
Modern-world robotics involves complex environments where multiple autonomous agents must interact with each other and other humans. This necessitates advanced interactive multi-agent motion planning techniques. Generalized Nash equilibrium(GNE), a s
Externí odkaz:
http://arxiv.org/abs/2410.05554
In the context of few-shot classification, the goal is to train a classifier using a limited number of samples while maintaining satisfactory performance. However, traditional metric-based methods exhibit certain limitations in achieving this objecti
Externí odkaz:
http://arxiv.org/abs/2409.07989
Autor:
Askari, Arian, Meng, Chuan, Aliannejadi, Mohammad, Ren, Zhaochun, Kanoulas, Evangelos, Verberne, Suzan
Existing generative retrieval (GR) approaches rely on training-based indexing, i.e., fine-tuning a model to memorise the associations between a query and the document identifier (docid) of a relevant document. Training-based indexing has three limita
Externí odkaz:
http://arxiv.org/abs/2408.02152
Autor:
Sabouri, Maziar, Ahamed, Shadab, Asadzadeh, Azin, Avval, Atlas Haddadi, Bagheri, Soroush, Arabi, Mohsen, Zakavi, Seyed Rasoul, Askari, Emran, Rasouli, Ali, Aghaee, Atena, Sehati, Mohaddese, Yousefirizi, Fereshteh, Uribe, Carlos, Hajianfar, Ghasem, Zaidi, Habib, Rahmim, Arman
The objective of this study was to develop an automated pipeline that enhances thyroid disease classification using thyroid scintigraphy images, aiming to decrease assessment time and increase diagnostic accuracy. Anterior thyroid scintigraphy images
Externí odkaz:
http://arxiv.org/abs/2407.10336
Autor:
Askari, Mohammad Taha, Lampe, Lutz
We introduce a practical sign-dependent sequence selection metric for probabilistic amplitude shaping and propose a simple method to predict the gains in signal-to-noise ratio (SNR) for sequence selection. The proposed metric provides a $0.5$ dB SNR
Externí odkaz:
http://arxiv.org/abs/2407.09006
Autor:
Kaushik, Pratiik, Askari, Koorosh, Gupta, Saksham, Mohan, Rahul, Skrinak, Kris, Kamyar, Royan, Smarr, Benjamin
Chronotype compares individuals' circadian phase to others. It contextualizes mental health risk assessments and detection of social jet lag, which can hamper mental health and cognitive performance. Existing ways of determining chronotypes, such as
Externí odkaz:
http://arxiv.org/abs/2407.06478
Self-correction in text-to-SQL is the process of prompting large language model (LLM) to revise its previously incorrectly generated SQL, and commonly relies on manually crafted self-correction guidelines by human experts that are not only labor-inte
Externí odkaz:
http://arxiv.org/abs/2406.12692
Autor:
Hemmat, Reyhane Askari, Hall, Melissa, Sun, Alicia, Ross, Candace, Drozdzal, Michal, Romero-Soriano, Adriana
With the growing popularity of text-to-image generative models, there has been increasing focus on understanding their risks and biases. Recent work has found that state-of-the-art models struggle to depict everyday objects with the true diversity of
Externí odkaz:
http://arxiv.org/abs/2406.04551
Large Language Models (LLMs) have achieved state-of-the-art performance at zero-shot generation of abstractive summaries for given articles. However, little is known about the robustness of such a process of zero-shot summarization. To bridge this ga
Externí odkaz:
http://arxiv.org/abs/2406.03993
Autor:
Bordes, Florian, Pang, Richard Yuanzhe, Ajay, Anurag, Li, Alexander C., Bardes, Adrien, Petryk, Suzanne, Mañas, Oscar, Lin, Zhiqiu, Mahmoud, Anas, Jayaraman, Bargav, Ibrahim, Mark, Hall, Melissa, Xiong, Yunyang, Lebensold, Jonathan, Ross, Candace, Jayakumar, Srihari, Guo, Chuan, Bouchacourt, Diane, Al-Tahan, Haider, Padthe, Karthik, Sharma, Vasu, Xu, Hu, Tan, Xiaoqing Ellen, Richards, Megan, Lavoie, Samuel, Astolfi, Pietro, Hemmat, Reyhane Askari, Chen, Jun, Tirumala, Kushal, Assouel, Rim, Moayeri, Mazda, Talattof, Arjang, Chaudhuri, Kamalika, Liu, Zechun, Chen, Xilun, Garrido, Quentin, Ullrich, Karen, Agrawal, Aishwarya, Saenko, Kate, Celikyilmaz, Asli, Chandra, Vikas
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guide us through unfamiliar environments to generative models that produce
Externí odkaz:
http://arxiv.org/abs/2405.17247