Natural Language Processing
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Phase transition in large language models and the criticality of natural languages
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AI-Driven Test Case Generation from Natural Language Requirements: A Survey of Techniques and Research Gaps
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How Much Do LLMs Know About Chinese Zero Pronouns?
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DySem: Uncovering Dynamic Semantic Components of Large Language Models for Calculating Semantic Textual Similarity
Announce Type: replace Abstract: Calculating semantic textual similarity is a foundational task in natural language processing. Current large language models (LLMs) based methods typically rely on extracting last-layer hidden states with fixed dimensions to compute similarity for every text pairs. We argue that this paradigm is suffer from two limitations: (i) The last hidden layer encodes more general knowledge rather than just semantic knowledge, making it suboptimal for semantic...
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KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts
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