Zobrazeno 1 - 10
of 3 240
pro vyhledávání: '"Chegini, A."'
Autor:
Chegini, Atoosa, Kazemi, Hamid, Mirzadeh, Iman, Yin, Dong, Horton, Maxwell, Nabi, Moin, Farajtabar, Mehrdad, Alizadeh, Keivan
In Large Language Model (LLM) development, Reinforcement Learning from Human Feedback (RLHF) is crucial for aligning models with human values and preferences. RLHF traditionally relies on the Kullback-Leibler (KL) divergence between the current polic
Externí odkaz:
http://arxiv.org/abs/2411.01798
Autor:
Sahu, Gaurav, Puri, Abhay, Rodriguez, Juan, Abaskohi, Amirhossein, Chegini, Mohammad, Drouin, Alexandre, Taslakian, Perouz, Zantedeschi, Valentina, Lacoste, Alexandre, Vazquez, David, Chapados, Nicolas, Pal, Christopher, Mudumba, Sai Rajeswar, Laradji, Issam Hadj
Data analytics is essential for extracting valuable insights from data that can assist organizations in making effective decisions. We introduce InsightBench, a benchmark dataset with three key features. First, it consists of 100 datasets representin
Externí odkaz:
http://arxiv.org/abs/2407.06423
We employ an inversion-based approach to examine CLIP models. Our examination reveals that inverting CLIP models results in the generation of images that exhibit semantic alignment with the specified target prompts. We leverage these inverted images
Externí odkaz:
http://arxiv.org/abs/2403.02580
Autor:
Sadasivan, Vinu Sankar, Saha, Shoumik, Sriramanan, Gaurang, Kattakinda, Priyatham, Chegini, Atoosa, Feizi, Soheil
In this paper, we introduce a novel class of fast, beam search-based adversarial attack (BEAST) for Language Models (LMs). BEAST employs interpretable parameters, enabling attackers to balance between attack speed, success rate, and the readability o
Externí odkaz:
http://arxiv.org/abs/2402.15570
Autor:
Chegini, Atoosa, Feizi, Soheil
Deep learning models can encounter unexpected failures, especially when dealing with challenging sub-populations. One common reason for these failures is the occurrence of objects in backgrounds that are rarely seen during training. To gain a better
Externí odkaz:
http://arxiv.org/abs/2312.05464
The locality of solution features in cardiac electrophysiology simulations calls for adaptive methods. Due to the overhead incurred by established mesh refinement and coarsening, however, such approaches failed in accelerating the computations. Here
Externí odkaz:
http://arxiv.org/abs/2311.07206
Autor:
Basu, Samyadeep, Saberi, Mehrdad, Bhardwaj, Shweta, Chegini, Atoosa Malemir, Massiceti, Daniela, Sanjabi, Maziar, Hu, Shell Xu, Feizi, Soheil
A plethora of text-guided image editing methods have recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models such as Imagen and Stable Diffusion. A standardized evaluation protocol, however,
Externí odkaz:
http://arxiv.org/abs/2310.02426
Autor:
Saberi, Mehrdad, Sadasivan, Vinu Sankar, Rezaei, Keivan, Kumar, Aounon, Chegini, Atoosa, Wang, Wenxiao, Feizi, Soheil
In light of recent advancements in generative AI models, it has become essential to distinguish genuine content from AI-generated one to prevent the malicious usage of fake materials as authentic ones and vice versa. Various techniques have been intr
Externí odkaz:
http://arxiv.org/abs/2310.00076
Autor:
Danial Fotros, Mohsen Shaygan Tabar, Maedeh Chegini, Mohammad Bahrizadeh, Amir Sadeghi, Amirhassan Rabbani, Zahra Yari, Azita Hekmatdoost
Publikováno v:
Journal of Health, Population and Nutrition, Vol 43, Iss 1, Pp 1-7 (2024)
Abstract Background The Dietary Approach to Stop Hypertension (DASH) has shown positive effects on various health factors that may be related to pancreatic steatosis (PS). This study aimed to investigate the association between adherence to the DASH
Externí odkaz:
https://doaj.org/article/7268084cd64a44f793aa366b15dd06db
Autor:
Raziye Chegini, Morteza Sadeghi, Sadegh Shirian, Fatemeh Sabbaghziarani, Ehsan Aali, Pouriya Soleimani, Mohammad Reza Ashtari Majelan, Fariba Zafari, Shahram Darabi
Publikováno v:
International Journal of Reproductive BioMedicine, Vol 22, Iss 7, Pp 527-538 (2024)
Abstract Background: Melatonin and L-carnitine are free radical scavengers with antiapoptotic and antioxidant properties that improve oocyte development. Objective: This study aimed to find the possible effect of combining 2 antioxidant agents of mel
Externí odkaz:
https://doaj.org/article/950e8d2f4eff4018bb452467d94c626d