Zobrazeno 1 - 10
of 8 366
pro vyhledávání: '"P Eslami"'
The recent excitement around generative models has sparked a wave of proposals suggesting the replacement of human participation and labor in research and development--e.g., through surveys, experiments, and interviews--with synthetic research data g
Externí odkaz:
http://arxiv.org/abs/2409.19430
Recently, an increasing number of news organizations have integrated artificial intelligence (AI) into their workflows, leading to a further influx of AI technologists and data workers into the news industry. This has initiated cross-functional colla
Externí odkaz:
http://arxiv.org/abs/2409.12000
Autor:
Hsieh, Jane, Zhang, Angie, Kim, Seyun, Rao, Varun Nagaraj, Dalal, Samantha, Mateescu, Alexandra, Grohmann, Rafael Do Nascimento, Eslami, Motahhare, Lee, Min Kyung, Zhu, Haiyi
Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulations. The CSCW and HCI communities increasingly turn to worker data col
Externí odkaz:
http://arxiv.org/abs/2409.00737
This paper presents a memristor-based compute-in-memory hardware accelerator for on-chip training and inference, focusing on its accuracy and efficiency against device variations, conductance errors, and input noise. Utilizing realistic SPICE models
Externí odkaz:
http://arxiv.org/abs/2408.14680
Autor:
Eslami, Navid, Dayan, Niv
Range filters are probabilistic data structures that answer approximate range emptiness queries. They aid in avoiding processing empty range queries and have use cases in many application domains such as key-value stores and social web analytics. How
Externí odkaz:
http://arxiv.org/abs/2408.05625
Autor:
Eslami, Sedigheh, de Melo, Gerard
Contrastive Language--Image Pre-training (CLIP) has manifested remarkable improvements in zero-shot classification and cross-modal vision-language tasks. Yet, from a geometrical point of view, the CLIP embedding space has been found to have a pronoun
Externí odkaz:
http://arxiv.org/abs/2406.17639
Autor:
Eslami, Mostafa, Babazadeh, Maryam
This paper introduces a novel global optimization algorithm called Particle Filter Optimization (PFO), designed for a class of stochastic problems. PFO leverages the Bayesian inference framework of Particle Filters (PF) by integrating the optimizatio
Externí odkaz:
http://arxiv.org/abs/2406.03089
Autor:
Hosseini, Maryam, Cipriano, Marco, Eslami, Sedigheh, Hodczak, Daniel, Liu, Liu, Sevtsuk, Andres, de Melo, Gerard
Why do some streets attract more social activities than others? Is it due to street design, or do land use patterns in neighborhoods create opportunities for businesses where people gather? These questions have intrigued urban sociologists, designers
Externí odkaz:
http://arxiv.org/abs/2406.01551
Autor:
Kim, Seyun, Fan, Bonnie, Yang, Willa Yunqi, Ramey, Jessie, Fox, Sarah E, Zhu, Haiyi, Zimmerman, John, Eslami, Motahhare
Technologies adopted by the public sector have transformed the work practices of employees in public agencies by creating different means of communication and decision-making. Although much of the recent research in the future of work domain has conc
Externí odkaz:
http://arxiv.org/abs/2405.18579
Autor:
Yang, Lin, Xu, Shawn, Sellergren, Andrew, Kohlberger, Timo, Zhou, Yuchen, Ktena, Ira, Kiraly, Atilla, Ahmed, Faruk, Hormozdiari, Farhad, Jaroensri, Tiam, Wang, Eric, Wulczyn, Ellery, Jamil, Fayaz, Guidroz, Theo, Lau, Chuck, Qiao, Siyuan, Liu, Yun, Goel, Akshay, Park, Kendall, Agharwal, Arnav, George, Nick, Wang, Yang, Tanno, Ryutaro, Barrett, David G. T., Weng, Wei-Hung, Mahdavi, S. Sara, Saab, Khaled, Tu, Tao, Kalidindi, Sreenivasa Raju, Etemadi, Mozziyar, Cuadros, Jorge, Sorensen, Gregory, Matias, Yossi, Chou, Katherine, Corrado, Greg, Barral, Joelle, Shetty, Shravya, Fleet, David, Eslami, S. M. Ali, Tse, Daniel, Prabhakara, Shruthi, McLean, Cory, Steiner, Dave, Pilgrim, Rory, Kelly, Christopher, Azizi, Shekoofeh, Golden, Daniel
Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Building upon Gemini's multimodal models, we develop several models within
Externí odkaz:
http://arxiv.org/abs/2405.03162