6 days ago · Our analysis provides compelling evidence that state- of-the-art embedding models struggle to capture domain-specific linguistic and semantic patterns, even ...
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Sep 4, 2024 · The methodology emerged from and is evaluated on a case study about the full-cycle prototype development of a domain-specific semantic search for daily ...
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Sep 15, 2024 · We demonstrate the effectiveness of AnnualBERT models by showing that they not only have comparable performances in standard tasks but also achieve state-of-the ...
Sep 25, 2024 · Figure 1 represents how some key indicators show that the shaped-up models (in blue) are more stable to prompt variation and are more correct, at the cost of ...
Sep 16, 2024 · The dataset initially created also undergoes data augmentation and is evaluated using metrics for semantic similarity. This study then benchmarked six LLMs on ...
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Sep 18, 2024 · The data challenges identified as problematic in other domains may be especially relevant to this discussion, given that the performance and accuracy of large- ...
3 days ago · ... variability language, for supporting the synthesis of model-based ... This paper reports about a new domain-specific variability modeling language ...
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Sep 20, 2024 · ... Semantic Textual Relatedness through Domain Adaptation and Ensemble Learning on BERT-based models ... Language Models (LLMs) in various languages and domains.
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Sep 24, 2024 · MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model Jiahao Huo, Yibo Yan, Boren Hu, Yutao Yue, Xuming Hu.
Sep 5, 2024 · the use of a common formalized language and their adaptation to the needs of particular businesses and organizations. ... Domain specific knowledge models, which ...
Missing: Variability | Show results with:Variability
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