Results 11 to 20 of about 3,989,044 (332)
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
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
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
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
CAESURA: Language Models as Multi-Modal Query Planners [PDF]
Conference on Innovative Data Systems Research, 2023 Traditional query planners translate SQL queries into query plans to be executed over relational data. However, it is impossible to query other data modalities, such as images, text, or video stored in modern data systems such as data lakes using these ...
Matthias Urban, Carsten Binnig
semanticscholar +1 more source
VLT: Vision-Language Transformer and Query Generation for Referring Segmentation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features.
Henghui Ding +3 more
semanticscholar +1 more source
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Multi-query attention (MQA), which only uses a single key-value head, drastically speeds up decoder inference. However, MQA can lead to quality degradation, and moreover it may not be desirable to train a separate model just for faster inference.
J. Ainslie +5 more
semanticscholar +1 more source
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning [PDF]
Neural Information Processing Systems, 2023 Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-language models is challenging due to the rich input distributions and task ...
Wenliang Dai +8 more
semanticscholar +1 more source
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