Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Geigle P"'
Recent Large Vision-Language Models (LVLMs) demonstrate impressive abilities on numerous image understanding and reasoning tasks. The task of fine-grained object classification (e.g., distinction between \textit{animal species}), however, has been pr
Externí odkaz:
http://arxiv.org/abs/2406.14496
Large vision-language models (LVLMs) have recently dramatically pushed the state of the art in image captioning and many image understanding tasks (e.g., visual question answering). LVLMs, however, often \textit{hallucinate} and produce captions that
Externí odkaz:
http://arxiv.org/abs/2406.14492
Image restoration is a fundamental problem that involves recovering a high-quality clean image from its degraded observation. All-In-One image restoration models can effectively restore images from various types and levels of degradation using degrad
Externí odkaz:
http://arxiv.org/abs/2401.16468
Modular vision-language models (Vision-LLMs) align pretrained image encoders with (frozen) large language models (LLMs) and post-hoc condition LLMs to `understand' the image input. With the abundance of readily available high-quality English image-te
Externí odkaz:
http://arxiv.org/abs/2307.06930
Vision-and-language (VL) models with separate encoders for each modality (e.g., CLIP) have become the go-to models for zero-shot image classification and image-text retrieval. They are, however, mostly evaluated in English as multilingual benchmarks
Externí odkaz:
http://arxiv.org/abs/2306.08658
Current multimodal models, aimed at solving Vision and Language (V+L) tasks, predominantly repurpose Vision Encoders (VE) as feature extractors. While many VEs -- of different architectures, trained on different data and objectives -- are publicly av
Externí odkaz:
http://arxiv.org/abs/2210.06379
Autor:
Baumgärtner, Tim, Wang, Kexin, Sachdeva, Rachneet, Eichler, Max, Geigle, Gregor, Poth, Clifton, Sterz, Hannah, Puerto, Haritz, Ribeiro, Leonardo F. R., Pfeiffer, Jonas, Reimers, Nils, Şahin, Gözde Gül, Gurevych, Iryna
Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e.g., extractive, abstractive), require different model architectures (e.g., generative, discriminative), and
Externí odkaz:
http://arxiv.org/abs/2203.13693
Autor:
María. Teresa Agulló-Ortuño, Helena Romay-Barrero, Johan Lambeck, Juan M. Blanco-Calonge, Rubén Arroyo-Fernández, Paula Richley Geigle, Raquel Menchero, Gonzalo Melgar del Corral, Inés Martínez-Galán
Publikováno v:
International Journal of Molecular Sciences, Vol 25, Iss 14, p 7961 (2024)
Spinal cord injury (SCI) is a severe medical condition resulting in substantial physiological and functional consequences for the individual. People with SCI are characterised by a chronic, low-grade systemic inflammatory state, which contributes to
Externí odkaz:
https://doaj.org/article/e52c7f30fb744d2082d27f68eacf382f
Autor:
Pfeiffer, Jonas, Geigle, Gregor, Kamath, Aishwarya, Steitz, Jan-Martin O., Roth, Stefan, Vulić, Ivan, Gurevych, Iryna
Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer modeling efforts. In this work, we address this gap and provide xGQA, a
Externí odkaz:
http://arxiv.org/abs/2109.06082
Question answering systems should help users to access knowledge on a broad range of topics and to answer a wide array of different questions. Most systems fall short of this expectation as they are only specialized in one particular setting, e.g., a
Externí odkaz:
http://arxiv.org/abs/2104.07081