Results 1 to 10 of about 3,730,229 (380)
Proceedings of the 1st International Workshop on Emerging Trends in Software Engineering for Blockchain, 2018 Blockchains store a massive amount of heterogeneous data which will only grow in time. When searching for data on the Ethereum platform, one is required to either access the records (blocks) directly by using a unique identifier, or sequentially search several records to find the desired information.
Bragagnolo, Santiago +3 more
openaire +2 more sources
The white matter query language: a novel approach for describing human white matter anatomy. [PDF]
Brain Struct Funct, 2016 We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion MRI volumes.
Wassermann D +6 more
europepmc +3 more sources
Context Definition and Query Language: Conceptual Specification, Implementation, and Evaluation [PDF]
Sensors, 2019 As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability.
Alireza Hassani +5 more
doaj +2 more sources
JMIR Medical Informatics, 2020 BackgroundEfforts are underway to semantically integrate large biomedical knowledge graphs using common upper-level ontologies to federate graph-oriented application programming interfaces (APIs) to the data. However, federation poses several challenges,
Cox, Steven +9 more
doaj +2 more sources
Query languages for neural networks [PDF]
We lay the foundations for a database-inspired approach to interpreting and understanding neural network models by querying them using declarative languages. Towards this end we study different query languages, based on first-order logic, that mainly differ in their access to the neural network model. First-order logic over the reals naturally yields a
Martin Grohe +3 more
openalex +4 more sources
Query2doc: Query Expansion with Large Language Models [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 This paper introduces a simple yet effective query expansion approach, denoted as query2doc, to improve both sparse and dense retrieval systems. The proposed method first generates pseudo-documents by few-shot prompting large language models (LLMs), and ...
Liang Wang, Nan Yang, Furu Wei
semanticscholar +1 more source
Query Rewriting for Retrieval-Augmented Large Language Models [PDF]
arXiv.org, 2023 Large Language Models (LLMs) play powerful, black-box readers in the retrieve-then-read pipeline, making remarkable progress in knowledge-intensive tasks.
Xinbei Ma +4 more
semanticscholar +1 more source
Prompting Is Programming: A Query Language for Large Language Models [PDF]
Proc. ACM Program. Lang., 2022 Large language models have demonstrated outstanding performance on a wide range of tasks such as question answering and code generation. On a high level, given an input, a language model can be used to automatically complete the sequence in a ...
Luca Beurer-Kellner +2 more
semanticscholar +1 more source
Vision-Language Transformer and Query Generation for Referring Segmentation [PDF]
IEEE International Conference on Computer Vision, 2021 In this work, we address the challenging task of referring segmentation. The query expression in referring segmentation typically indicates the target object by describing its relationship with others.
Henghui Ding +3 more
semanticscholar +1 more source
Query Expansion by Prompting Large Language Models [PDF]
arXiv.org, 2023 Query expansion is a widely used technique to improve the recall of search systems. In this paper, we propose an approach to query expansion that leverages the generative abilities of Large Language Models (LLMs).
R. Jagerman +4 more
semanticscholar +1 more source