Zobrazeno 1 - 10
of 180
pro vyhledávání: '"De Melo, Gerard"'
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 10:1-10:19 (2023)
There is a lack of multilingual data to support applications in a large number of languages, especially for low-resource languages. Knowledge graphs (KG) could contribute to closing the gap of language support by providing easily accessible, machine-
Externí odkaz:
https://doaj.org/article/39b7d746b98243f7b3ae1b8abbb6fda4
Autor:
Biswas, Russa, Kaffee, Lucie-Aimée, Cochez, Michael, Dumbrava, Stefania, Jendal, Theis E., Lissandrini, Matteo, Lopez, Vanessa, Mencía, Eneldo Loza, Paulheim, Heiko, Sack, Harald, Vakaj, Edlira Kalemi, de Melo, Gerard
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 4:1-4:32 (2023)
While Knowledge Graphs (KGs) have long been used as valuable sources of structured knowledge, in recent years, KG embeddings have become a popular way of deriving numeric vector representations from them, for instance, to support knowledge graph comp
Externí odkaz:
https://doaj.org/article/5ecb460fc50c4c999be30b70ac3bb957
Autor:
Pan, Jeff Z., Razniewski, Simon, Kalo, Jan-Christoph, Singhania, Sneha, Chen, Jiaoyan, Dietze, Stefan, Jabeen, Hajira, Omeliyanenko, Janna, Zhang, Wen, Lissandrini, Matteo, Biswas, Russa, de Melo, Gerard, Bonifati, Angela, Vakaj, Edlira, Dragoni, Mauro, Graux, Damien
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 2:1-2:38 (2023)
Large Language Models (LLMs) have taken Knowledge Representation - and the world - by storm. This inflection point marks a shift from explicit knowledge representation to a renewed focus on the hybrid representation of both explicit knowledge and par
Externí odkaz:
https://doaj.org/article/49afd43227ff4798bd12c458ce0158d0
Scalable Vector Graphics (SVG) is a popular format on the web and in the design industry. However, despite the great strides made in generative modeling, SVG has remained underexplored due to the discrete and complex nature of such data. We introduce
Externí odkaz:
http://arxiv.org/abs/2410.05991
Autor:
Ouyang, Zetian, Qiu, Yishuai, Wang, Linlin, de Melo, Gerard, Zhang, Ya, Wang, Yanfeng, He, Liang
With the proliferation of Large Language Models (LLMs) in diverse domains, there is a particular need for unified evaluation standards in clinical medical scenarios, where models need to be examined very thoroughly. We present CliMedBench, a comprehe
Externí odkaz:
http://arxiv.org/abs/2410.03502
Autor:
Dobler, Konstantin, de Melo, Gerard
We investigate continued pretraining of LLMs for language adaptation on a tight academic budget: a setting in which only a few GPUs can be used in parallel, for a heavily constrained duration. We focus on adapting Mistral-7B to German or Arabic and e
Externí odkaz:
http://arxiv.org/abs/2408.15793
Autor:
Owoyele, Babajide Alamu, Schilling, Martin, Sawahn, Rohan, Kaemer, Niklas, Zherebenkov, Pavel, Verma, Bhuvanesh, Pouw, Wim, de Melo, Gerard
This paper introduces MaskAnyone, a novel toolkit designed to navigate some privacy and ethical concerns of sharing audio-visual data in research. MaskAnyone offers a scalable, user-friendly solution for de-identifying individuals in video and audio
Externí odkaz:
http://arxiv.org/abs/2408.03185
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:
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:
Buz, Tolga, Frost, Benjamin, Genchev, Nikola, Schneider, Moritz, Kaffee, Lucie-Aimée, de Melo, Gerard
Recent Large Language Models (LLMs) have shown the ability to generate content that is difficult or impossible to distinguish from human writing. We investigate the ability of differently-sized LLMs to replicate human writing style in short, creative
Externí odkaz:
http://arxiv.org/abs/2405.01660