Zobrazeno 1 - 10
of 6 379
pro vyhledávání: '"Ignat, A."'
Unequal representation across cultures and socioeconomic groups in AI is a significant and challenging problem, often leading to uneven model performance. As a step toward addressing this issue, we formulate translated non-English, geographic, and so
Externí odkaz:
http://arxiv.org/abs/2407.02623
Reinforcement Learning (RL) has achieved impressive results on complex tasks but struggles in multi-task settings with different embodiments. World models offer scalability by learning a simulation of the environment, yet they often rely on inefficie
Externí odkaz:
http://arxiv.org/abs/2407.02466
Autor:
Romero, David, Lyu, Chenyang, Wibowo, Haryo Akbarianto, Lynn, Teresa, Hamed, Injy, Kishore, Aditya Nanda, Mandal, Aishik, Dragonetti, Alina, Abzaliev, Artem, Tonja, Atnafu Lambebo, Balcha, Bontu Fufa, Whitehouse, Chenxi, Salamea, Christian, Velasco, Dan John, Adelani, David Ifeoluwa, Meur, David Le, Villa-Cueva, Emilio, Koto, Fajri, Farooqui, Fauzan, Belcavello, Frederico, Batnasan, Ganzorig, Vallejo, Gisela, Caulfield, Grainne, Ivetta, Guido, Song, Haiyue, Ademtew, Henok Biadglign, Maina, Hernán, Lovenia, Holy, Azime, Israel Abebe, Cruz, Jan Christian Blaise, Gala, Jay, Geng, Jiahui, Ortiz-Barajas, Jesus-German, Baek, Jinheon, Dunstan, Jocelyn, Alemany, Laura Alonso, Nagasinghe, Kumaranage Ravindu Yasas, Benotti, Luciana, D'Haro, Luis Fernando, Viridiano, Marcelo, Estecha-Garitagoitia, Marcos, Cabrera, Maria Camila Buitrago, Rodríguez-Cantelar, Mario, Jouitteau, Mélanie, Mihaylov, Mihail, Imam, Mohamed Fazli Mohamed, Adilazuarda, Muhammad Farid, Gochoo, Munkhjargal, Otgonbold, Munkh-Erdene, Etori, Naome, Niyomugisha, Olivier, Silva, Paula Mónica, Chitale, Pranjal, Dabre, Raj, Chevi, Rendi, Zhang, Ruochen, Diandaru, Ryandito, Cahyawijaya, Samuel, Góngora, Santiago, Jeong, Soyeong, Purkayastha, Sukannya, Kuribayashi, Tatsuki, Jayakumar, Thanmay, Torrent, Tiago Timponi, Ehsan, Toqeer, Araujo, Vladimir, Kementchedjhieva, Yova, Burzo, Zara, Lim, Zheng Wei, Yong, Zheng Xin, Ignat, Oana, Nwatu, Joan, Mihalcea, Rada, Solorio, Thamar, Aji, Alham Fikri
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual and textual data. However, most of the current VQA
Externí odkaz:
http://arxiv.org/abs/2406.05967
Autor:
Paris, Luis, Soroko, Ignat
We determine a classification of the endomorphisms of the Artin group of affine type $\tilde A_n$ for $n\ge 4$.
Comment: v2: a reference added, 19 pages, 6 figures
Comment: v2: a reference added, 19 pages, 6 figures
Externí odkaz:
http://arxiv.org/abs/2406.02484
In this paper, we present a novel methodology we call MDS-ViTNet (Multi Decoder Saliency by Vision Transformer Network) for enhancing visual saliency prediction or eye-tracking. This approach holds significant potential for diverse fields, including
Externí odkaz:
http://arxiv.org/abs/2405.19501
Model-Free Reinforcement Learning (MFRL), leveraging the policy gradient theorem, has demonstrated considerable success in continuous control tasks. However, these approaches are plagued by high gradient variance due to zeroth-order gradient estimati
Externí odkaz:
http://arxiv.org/abs/2405.17784
Deceptive reviews are becoming increasingly common, especially given the increase in performance and the prevalence of LLMs. While work to date has addressed the development of models to differentiate between truthful and deceptive human reviews, muc
Externí odkaz:
http://arxiv.org/abs/2404.12938
Inspiration is linked to various positive outcomes, such as increased creativity, productivity, and happiness. Although inspiration has great potential, there has been limited effort toward identifying content that is inspiring, as opposed to just en
Externí odkaz:
http://arxiv.org/abs/2404.12933
Synthetic data generation has the potential to impact applications and domains with scarce data. However, before such data is used for sensitive tasks such as mental health, we need an understanding of how different demographics are represented in it
Externí odkaz:
http://arxiv.org/abs/2403.16909
Current foundation models have shown impressive performance across various tasks. However, several studies have revealed that these models are not effective for everyone due to the imbalanced geographical and economic representation of the data used
Externí odkaz:
http://arxiv.org/abs/2403.07687