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Articles by de Lacalle
Computer Science > Computation and Language
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Do not be greedy, Think Twice: Sampling and Selection for Document-level Information Extraction
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
[2512.08713] Automatic Essay Scoring and Feedback Generation in Basque Language Learning
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
[2503.01851] Euskarazko lehen C1 ebaluatzaile automatikoa
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
arXiv:2310.03668 (cs) [Submitted on 5 Oct 2023 (v1), last revised 6 Mar 2024 (this version, v5)] Download PDF HTML (experimental) Comments: Subjects: Computation and Language (cs.CL) Cite as: arXiv:2310.03668 [cs.CL] (or arXiv:2310.03668v5 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2310.03668 Submission history From: Iker García-Ferrero [ view email] [v1] Thu, 5 Oct 2023 16:43:13 UTC (9,011 KB) [v2] Fri, 6 Oct 2023 17:41:15 UTC (9,011 KB) [v3] Mon, 11 Dec 2023 08:24:40 UTC...
[2308.01223] Do Multilingual Language Models Think Better in English?
Translate-test is a popular technique to improve the performance of multilingual language models. This approach works by translating the input into English using an external machine translation system, and running inference over the translated input. However, these improvements can be attributed to the use of a separate translation system, which is typically trained on large amounts of parallel data not seen by the language model.
On the effects of cutting-edge angle on high-feed turning of Inconel 718© superalloy - The International Journal of Advanced Manufacturing Technology
Abstract Machining processes on heat-resistant superalloys—i.e., turbine cases, rings, or shafts—are challenging tasks. The high-added value of such parts makes cycle times be longer than expected. Recently, high-feed turning technique has attracted the attention of practitioners due to its high material removal rate capability. PrimeTurning™ tool unifies the concepts of high-feed and multidirectional turning using multiple active cutting edges.
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