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pro vyhledávání: '"Ortíz, Alberto"'
We explore the potential of pixel-based models for transfer learning from standard languages to dialects. These models convert text into images that are divided into patches, enabling a continuous vocabulary representation that proves especially usef
Externí odkaz:
http://arxiv.org/abs/2412.09084
Since the influential work of ten Wolde, Ruiz-Montero, and Frenkel [Phys. Rev. Lett. 75, 2714 (1995)], crystal nucleation from a Lennard-Jones fluid has been regarded as a paradigmatic example of metastable crystal ordering at the surface of a critic
Externí odkaz:
http://arxiv.org/abs/2412.03276
Optimizing the synthesis of zeolites and exploring novel frameworks offer pivotal opportunities and challenges in materials design. While inverse design proves highly effective for simpler crystals, its application to intricate structures like zeolit
Externí odkaz:
http://arxiv.org/abs/2410.22111
Autor:
Bedolla-Montiel, Edwin A., Lange, Jochem T., Ortíz, Alberto Pérez de Alba, Dijkstra, Marjolein
The development of new materials typically involves a process of trial and error, guided by insights from past experimental and theoretical findings. The inverse design approach for soft-matter systems has the potential to optimize specific physical
Externí odkaz:
http://arxiv.org/abs/2403.15277
Specialized compute blocks have been developed for efficient DNN execution. However, due to the vast amount of data and parameter movements, the interconnects and on-chip memories form another bottleneck, impairing power and performance. This work ad
Externí odkaz:
http://arxiv.org/abs/2311.05557
We present an approach for assessing how multilingual large language models (LLMs) learn syntax in terms of multi-formalism syntactic structures. We aim to recover constituent and dependency structures by casting parsing as sequence labeling. To do s
Externí odkaz:
http://arxiv.org/abs/2309.11165
Publikováno v:
Artificial Intelligence Review 57, 265 (2024)
We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different families and four sizes in total. Our analysis spans several measurabl
Externí odkaz:
http://arxiv.org/abs/2308.09067
Autor:
Muñoz-Ortiz, Alberto, Vilares, David
The usefulness of part-of-speech tags for parsing has been heavily questioned due to the success of word-contextualized parsers. Yet, most studies are limited to coarse-grained tags and high quality written content; while we know little about their i
Externí odkaz:
http://arxiv.org/abs/2305.15119
Boltzmann generators (BGs) are now recognized as forefront generative models for sampling equilibrium states of many-body systems in the canonical ensemble, as well as for calculating the corresponding Helmholtz free energy. Furthermore, BGs can pote
Externí odkaz:
http://arxiv.org/abs/2305.08483
PoS tags, once taken for granted as a useful resource for syntactic parsing, have become more situational with the popularization of deep learning. Recent work on the impact of PoS tags on graph- and transition-based parsers suggests that they are on
Externí odkaz:
http://arxiv.org/abs/2210.15219