Zobrazeno 1 - 10
of 6 290
pro vyhledávání: '"Ignat BE"'
Autor:
Bagajo, Joshua, Schwarke, Clemens, Klemm, Victor, Georgiev, Ignat, Sleiman, Jean-Pierre, Tordesillas, Jesus, Garg, Animesh, Hutter, Marco
Differentiable simulators provide analytic gradients, enabling more sample-efficient learning algorithms and paving the way for data intensive learning tasks such as learning from images. In this work, we demonstrate that locomotion policies trained
Externí odkaz:
http://arxiv.org/abs/2411.02189
Autor:
Mihalcea, Rada, Ignat, Oana, Bai, Longju, Borah, Angana, Chiruzzo, Luis, Jin, Zhijing, Kwizera, Claude, Nwatu, Joan, Poria, Soujanya, Solorio, Thamar
This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation. We address key limitations in the current AI pipeline and its WEIRD representation, such as la
Externí odkaz:
http://arxiv.org/abs/2410.16315
Autor:
Soroko, Ignat, Vaskou, Nicolas
We establish property $R_\infty$ for Artin groups of spherical type $D_n$, $n\ge6$, their central quotients, and also for large hyperbolic-type free-of-infinity Artin groups and some other classes of large-type Artin groups. The key ingredients are r
Externí odkaz:
http://arxiv.org/abs/2409.18123
Autor:
Paris, Luis, Soroko, Ignat
We determine a classification of the endomorphisms of the Artin groups of spherical type $B_n$ for $n\ge 5$, and of their quotients by the center.
Comment: 27 pages, 6 figures. arXiv admin note: text overlap with arXiv:2406.02484
Comment: 27 pages, 6 figures. arXiv admin note: text overlap with arXiv:2406.02484
Externí odkaz:
http://arxiv.org/abs/2409.12552
Autor:
Ignat, Radu
We give a short and self-contained proof of the interior $\mathcal C^{1,1}$ regularity of solutions $\varphi:\Omega \to \mathbb{R}$ to the eikonal equation $|\nabla \varphi|=1$ in an open set $\Omega\subset \mathbb{R}^{N}$ in dimension $N\geq 1$ unde
Externí odkaz:
http://arxiv.org/abs/2409.05204
Recent work has demonstrated that the unequal representation of cultures and socioeconomic groups in training data leads to biased Large Multi-modal (LMM) models. To improve LMM model performance on underrepresented data, we propose and evaluate seve
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, Clifford, Teresa, 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: v3: Corollary 3.6 added; v2: a reference added, 19 pages, 6 figures
Comment: v3: Corollary 3.6 added; 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