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pro vyhledávání: '"Ormazábal, A"'
Despite the impressive performance of autoregressive Language Models (LM) it has been shown that due to reporting bias, LMs lack visual knowledge, i.e. they do not know much about the visual world and its properties. To augment LMs with visual knowle
Externí odkaz:
http://arxiv.org/abs/2409.11148
Autor:
Padlewski, Piotr, Bain, Max, Henderson, Matthew, Zhu, Zhongkai, Relan, Nishant, Pham, Hai, Ong, Donovan, Aleksiev, Kaloyan, Ormazabal, Aitor, Phua, Samuel, Yeo, Ethan, Lamprecht, Eugenie, Liu, Qi, Wang, Yuqi, Chen, Eric, Fu, Deyu, Li, Lei, Zheng, Che, d'Autume, Cyprien de Masson, Yogatama, Dani, Artetxe, Mikel, Tay, Yi
We introduce Vibe-Eval: a new open benchmark and framework for evaluating multimodal chat models. Vibe-Eval consists of 269 visual understanding prompts, including 100 of hard difficulty, complete with gold-standard responses authored by experts. Vib
Externí odkaz:
http://arxiv.org/abs/2405.02287
Autor:
Reka Team, Ormazabal, Aitor, Zheng, Che, d'Autume, Cyprien de Masson, Yogatama, Dani, Fu, Deyu, Ong, Donovan, Chen, Eric, Lamprecht, Eugenie, Pham, Hai, Ong, Isaac, Aleksiev, Kaloyan, Li, Lei, Henderson, Matthew, Bain, Max, Artetxe, Mikel, Relan, Nishant, Padlewski, Piotr, Liu, Qi, Chen, Ren, Phua, Samuel, Yang, Yazheng, Tay, Yi, Wang, Yuqi, Zhu, Zhongkai, Xie, Zhihui
We introduce Reka Core, Flash, and Edge, a series of powerful multimodal language models trained from scratch by Reka. Reka models are able to process and reason with text, images, video, and audio inputs. This technical report discusses details of t
Externí odkaz:
http://arxiv.org/abs/2404.12387
Autor:
Etxaniz, Julen, Sainz, Oscar, Perez, Naiara, Aldabe, Itziar, Rigau, German, Agirre, Eneko, Ormazabal, Aitor, Artetxe, Mikel, Soroa, Aitor
Publikováno v:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 14952--14972. 2024
We introduce Latxa, a family of large language models for Basque ranging from 7 to 70 billion parameters. Latxa is based on Llama 2, which we continue pretraining on a new Basque corpus comprising 4.3M documents and 4.2B tokens. Addressing the scarci
Externí odkaz:
http://arxiv.org/abs/2403.20266
Publikováno v:
22nd Portuguese Conference on Artificial Intelligence (EPIA 2023)
We present Erato, a framework designed to facilitate the automated evaluation of poetry, including that generated by poetry generation systems. Our framework employs a diverse set of features, and we offer a brief overview of Erato's capabilities and
Externí odkaz:
http://arxiv.org/abs/2310.20326
Methods for adapting language models (LMs) to new tasks and domains have traditionally assumed white-box access to the model, and work by modifying its parameters. However, this is incompatible with a recent trend in the field, where the highest qual
Externí odkaz:
http://arxiv.org/abs/2305.16876
Round-trip Machine Translation (MT) is a popular choice for paraphrase generation, which leverages readily available parallel corpora for supervision. In this paper, we formalize the implicit similarity function induced by this approach, and show tha
Externí odkaz:
http://arxiv.org/abs/2205.12213
Formal verse poetry imposes strict constraints on the meter and rhyme scheme of poems. Most prior work on generating this type of poetry uses existing poems for supervision, which are difficult to obtain for most languages and poetic forms. In this w
Externí odkaz:
http://arxiv.org/abs/2205.12206
Publikováno v:
In Sustainable Production and Consumption October 2024 50:253-267
Autor:
Bravo, M.E., Principi, S., Levin, L.A., Ormazabal, J.P., Ferronato, C., Palma, F., Isola, J., Tassone, A.A.
Publikováno v:
In Deep-Sea Research Part I September 2024 211