Nearest Neighbor Search (NNS) is a fundamental problem in data structures with wide-ranging applications, such as web search, recommendation systems, and, more recently, retrieval-augmented ...
ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The discovery of functional small molecules, chemical matter ...
ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...
Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...
Nearest neighbour classification techniques, particularly the k‐nearest neighbour (kNN) algorithm, have long been valued for their simplicity and effectiveness in pattern recognition and data ...
Mikel Hernaez receives funding from the Spanish Ministry of Science, Innovation and Universities, the government of Navarra, the EU Department of Defence, the Carlos III Health Institute and the ...
Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...
Abstract: In education, for topics delivery still has abstract characteristic. That abstract means the topic cannot be explained in picture and text only. One of the topics is human body's system.
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