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pro vyhledávání: '"Eger, P"'
Recent research has focused on literary machine translation (MT) as a new challenge in MT. However, the evaluation of literary MT remains an open problem. We contribute to this ongoing discussion by introducing LITEVAL-CORPUS, a paragraph-level paral
Externí odkaz:
http://arxiv.org/abs/2410.18697
Autor:
Zhang, Ran, Eger, Steffen
Despite substantial progress of large language models (LLMs) for automatic poetry generation, the generated poetry lacks diversity while the training process differs greatly from human learning. Under the rationale that the learning process of the po
Externí odkaz:
http://arxiv.org/abs/2409.03659
In therapeutic focused ultrasound (FUS), such as thermal ablation and hyperthermia, effective acousto-thermal manipulation requires precise targeting of complex geometries, sound wave propagation through irregular structures and selective focusing at
Externí odkaz:
http://arxiv.org/abs/2409.01323
Autor:
Leiter, Christoph, Eger, Steffen
Large language models (LLMs) have revolutionized the field of NLP. Notably, their in-context learning capabilities also enable their use as evaluation metrics for natural language generation, making them particularly advantageous in low-resource scen
Externí odkaz:
http://arxiv.org/abs/2406.18528
Natural Language Generation (NLG), and more generally generative AI, are among the currently most impactful research fields. Creative NLG, such as automatic poetry generation, is a fascinating niche in this area. While most previous research has focu
Externí odkaz:
http://arxiv.org/abs/2406.15267
State-of-the-art trainable machine translation evaluation metrics like xCOMET achieve high correlation with human judgment but rely on large encoders (up to 10.7B parameters), making them computationally expensive and inaccessible to researchers with
Externí odkaz:
http://arxiv.org/abs/2406.14553
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
Structured science summaries or research contributions using properties or dimensions beyond traditional keywords enhances science findability. Current methods, such as those used by the Open Research Knowledge Graph (ORKG), involve manually curating
Externí odkaz:
http://arxiv.org/abs/2405.02105
Autor:
Chen, Yanran, Zhao, Wei, Breitbarth, Anne, Stoeckel, Manuel, Mehler, Alexander, Eger, Steffen
Many studies have shown that human languages tend to optimize for lower complexity and increased communication efficiency. Syntactic dependency distance, which measures the linear distance between dependent words, is often considered a key indicator
Externí odkaz:
http://arxiv.org/abs/2402.11549
Autor:
Nguyen, Hoa, Eger, Steffen
Citations are a key ingredient of scientific research to relate a paper to others published in the community. Recently, it has been noted that there is a citation age bias in the Natural Language Processing (NLP) community, one of the currently faste
Externí odkaz:
http://arxiv.org/abs/2401.03545