SPEC CPU 2026 presents a new benchmark suite using open-source apps, expanded multithreading, and Rolling-Round-Robin Rate to address gaps in evaluating heterogeneous multiprogrammed CPU performance.
Marian: Fast Neural Machine Translation in C++
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Marian is written entirely in C++. We describe the design of the encoder-decoder framework and demonstrate that a research-friendly toolkit can achieve high training and translation speed.
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Hugging Face releases an open-source Python library that supplies a unified API and pretrained weights for major Transformer architectures used in natural language processing.
Development of domain-specific scientific corpora for English-Spanish, English-French, and English-Portuguese and their application to fine-tuning NMT models.
Verbal multiword expressions reduce machine translation quality, with the degradation attributable to the expressions themselves rather than general sentence difficulty.
citing papers explorer
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SPEC CPU: The Next Generation
SPEC CPU 2026 presents a new benchmark suite using open-source apps, expanded multithreading, and Rolling-Round-Robin Rate to address gaps in evaluating heterogeneous multiprogrammed CPU performance.
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HuggingFace's Transformers: State-of-the-art Natural Language Processing
Hugging Face releases an open-source Python library that supplies a unified API and pretrained weights for major Transformer architectures used in natural language processing.
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Enhancing Scientific Discourse: Machine Translation for the Scientific Domain
Development of domain-specific scientific corpora for English-Spanish, English-French, and English-Portuguese and their application to fine-tuning NMT models.
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Evaluating the Impact of Verbal Multiword Expressions on Machine Translation
Verbal multiword expressions reduce machine translation quality, with the degradation attributable to the expressions themselves rather than general sentence difficulty.