Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Belouadi, Jonas"'
Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equall
Externí odkaz:
http://arxiv.org/abs/2405.15306
Autor:
Zhang, Ran, Kostikova, Aida, Leiter, Christoph, Belouadi, Jonas, Larionov, Daniil, Chen, Yanran, Fresen, Vivian, Eger, Steffen
Artificial Intelligence (AI) has witnessed rapid growth, especially in the subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer Vision (CV). Keeping pace with this rapid progress poses a considerable challenge for researche
Externí odkaz:
http://arxiv.org/abs/2312.05688
Publikováno v:
The Twelfth International Conference on Learning Representations, 2024
Generating bitmap graphics from text has gained considerable attention, yet for scientific figures, vector graphics are often preferred. Given that vector graphics are typically encoded using low-level graphics primitives, generating them directly is
Externí odkaz:
http://arxiv.org/abs/2310.00367
Autor:
Eger, Steffen, Leiter, Christoph, Belouadi, Jonas, Zhang, Ran, Kostikova, Aida, Larionov, Daniil, Chen, Yanran, Fresen, Vivian
The rapid growth of information in the field of Generative Artificial Intelligence (AI), particularly in the subfields of Natural Language Processing (NLP) and Machine Learning (ML), presents a significant challenge for researchers and practitioners
Externí odkaz:
http://arxiv.org/abs/2308.04889
Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide att
Externí odkaz:
http://arxiv.org/abs/2306.04314
Autor:
Leiter, Christoph, Zhang, Ran, Chen, Yanran, Belouadi, Jonas, Larionov, Daniil, Fresen, Vivian, Eger, Steffen
ChatGPT, a chatbot developed by OpenAI, has gained widespread popularity and media attention since its release in November 2022. However, little hard evidence is available regarding its perception in various sources. In this paper, we analyze over 30
Externí odkaz:
http://arxiv.org/abs/2302.13795
Autor:
Belouadi, Jonas, Eger, Steffen
State-of-the-art poetry generation systems are often complex. They either consist of task-specific model pipelines, incorporate prior knowledge in the form of manually created constraints, or both. In contrast, end-to-end models would not suffer from
Externí odkaz:
http://arxiv.org/abs/2212.10474
Reproducibility is of utmost concern in machine learning and natural language processing (NLP). In the field of natural language generation (especially machine translation), the seminal paper of Post (2018) has pointed out problems of reproducibility
Externí odkaz:
http://arxiv.org/abs/2204.00004
Autor:
Belouadi, Jonas, Eger, Steffen
The vast majority of evaluation metrics for machine translation are supervised, i.e., (i) are trained on human scores, (ii) assume the existence of reference translations, or (iii) leverage parallel data. This hinders their applicability to cases whe
Externí odkaz:
http://arxiv.org/abs/2202.10062
Autor:
Leiter, Christoph, Zhang, Ran, Chen, Yanran, Belouadi, Jonas, Larionov, Daniil, Fresen, Vivian, Eger, Steffen
Publikováno v:
In Machine Learning with Applications June 2024 16
