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1. Soft cosine and extended cosine adaptation for pre-trained language model semantic vector analysis NSTL国家科技图书文献中心

Ijebu, Funebi Franci... |  Liu, Yuanchao... -  《Applied Soft Computing》 - 2025,169 - 共15页

摘要：Semantic textual analysis is a natural |  textual similarity analysis. A plethora of solutions |  textual similarity tasks, under same conditions, for the |  problems. Vector comparison is a core subtask in semantic |  focused on using only cosine similarity for embedding
关键词： Transformer-based model |  Large language model |  Vector space model |  Transfer learning |  Semantic textual similarity
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2. Evaluating the Performance of LLMs When Translating Saudi Arabic as Low Resource Language NSTL国家科技图书文献中心

Salwa Alahmari |  Eric Atwell... -  《Artificial Intelligence XLI,Part II》 -  SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence - 2025, - 264～269 - 共6页

摘要： these LLMs on the Arabic Semantic Textual Similarity |  textual data from Saudi Arabic, a low-resource language | This paper evaluates the performance of |  different large language models (LLMs) in translating | , into English. In this investigation we employ the
关键词： ChatGPT |  Claude |  Palm |  Large language models |  Evaluation of AI systems |  Machine translation |  Saudi arabic dialect
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3. SPCSE: Soft Positive Enhanced Contrastive Learning for Sentence Embeddings NSTL国家科技图书文献中心

Lingen Liu |  Zixin Chen... -  《Pattern Recognition,Part IX》 -  International Conference on Pattern Recognition - 2025, - 322～336 - 共15页

摘要： Textual Similarity (STS) tasks demonstrate that SPCSE |  suffer from the limitation of minimal semantic changes | . Our experimental results across seven Semantic | Unsupervised contrastive learning for high | -quality sentence representations has gained widespread
关键词： Sentence representation learning |  Unsupervised learning |  Soft positives
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4. Efficient Semantic Trajectory Similarity Search NSTL国家科技图书文献中心

Jian Chen |  Hong Gao... -  《IEEE internet of things journal》 - 2025,12(2) - 2219～2232 - 共14页

摘要： threshold $theta $ , semantic trajectory similarity |  the search space by spatial and textual similarity |  bounds on textual and spatial similarity for pruning | Trajectory similarity search is a basic |  with their trajectories, called semantic trajectories
关键词： Trajectory |  Semantics |  Internet of Things |  Indexes |  Filtering |  Search problems |  Shape
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5. ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched Embeddings NSTL国家科技图书文献中心

Jangyeong Jeon |  Sangyeon Cho... -  《Pattern Recognition,Part XX》 -  International Conference on Pattern Recognition - 2025, - 29～44 - 共16页

摘要： (Semantic Textual Similarity) tasks. (Source code | This paper examines the Code-Switching (CS | ) phenomenon where two languages intertwine within a single |  utterance. There exists a noticeable need for research on |  the CS between English and Korean. We highlight that
关键词： Natural language processing |  Contrastive learning |  Code-Switching |  Bilingual |  Koglish dataset
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6. Cluster-Mined Negative Samples for Enhanced Unsupervised Sentence Representation Learning NSTL国家科技图书文献中心

Yuhang Zhang |  Wenjie Zhang... -  《Pattern Recognition,Part XXVI》 -  International Conference on Pattern Recognition - 2025, - 440～456 - 共17页

摘要： representation, especially for semantic textual similarity | Negative samples selection for contrastive |  learning is considerable in the field of sentence | . Traditional in-batch negative sampling methods not only lack |  hard negative samples but also ignore potential false
关键词： Sentence representation |  Contrastive learning |  Clustering |  Negative sampling |  Semantic text similarity
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7. Efficient Parallel Processing of Semantic Trajectory Similarity Joins NSTL国家科技图书文献中心

Shuo Shang |  Chengrui Huang... -  《IEEE internet of things journal》 - 2025,12(4) - 3534～3548 - 共15页

摘要： sets with spatio-textual similarity no less than |  derive bounds of spatial similarity and textual |  similarity between two semantic trajectories, which enable |  trajectory similarity join, is a fundamental functionality |  increasingly popular. In this light, we investigate semantic
关键词： Trajectory |  Semantics |  Filtering |  Web sites |  Social networking (online) |  Partitioning algorithms |  Multimedia communication
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8. Label Semantic Dynamic Guidance Network for Remote Sensing Image Scene Classification NSTL国家科技图书文献中心

Borui Chai |  Tianming Zhao... -  《IEEE Transactions on Geoscience and Remote Sensing》 - 2025,63 - 1～14 - 共14页

摘要： intraclass diversity and interclass similarity. Existing |  methods mainly use semantic associations between images |  to establish deep semantic associations between |  classes, ignoring the rich high-level semantic knowledge |  both similarity and distinctive features effectively
关键词： Semantics |  Remote sensing |  Feature extraction |  Scene classification |  Vectors |  Training |  Data mining |  Correlation |  Measurement |  Contrastive learning
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9. FEAttack: A Fast and Efficient Hard-Label Textual Attack Framework NSTL国家科技图书文献中心

Miaomiao Li |  Jun Ma... -  《Wireless Artificial Intelligent Computing Systems and Applications,Part II》 -  International Conference on Wireless Artificial Intelligent Computing Systems and Applications - 2025, - 167～179 - 共13页

摘要： examples quickly with higher semantic similarity and | Hard-label textual attacks are realistic but | -label textual Attack framework for generating high |  greedily replacing with synonyms to improve the semantic |  similarity. Extensive experimental results on three typical
关键词： Hard-label |  Textual attack |  Two-stage optimization
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10. Efficient Image Search and Retrieval System in Cloud Platforms NSTL国家科技图书文献中心

Francisco Izquierdo |  Cesar Analide... -  《Progress in Artificial Intelligence,Part II》 -  EPIA Conference on Artificial Intelligence - 2025, - 362～373 - 共12页

摘要： search by similarity of textual description based on |  searches for the user. The solution focuses on semantic |  ability to understand semantic relationships between |  using textual annotations generated by a model capable |  semantics of textual data. The proposed system aims to
关键词： Cloud platforms |  Images |  Search |  Artificial intelligence |  Semantic relationships
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