Supplementary Material for Retro-Li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization

This is the supplementary material of the paper accepted with the same title in the 27th European Conference on Artificial Intelligence (ECAI), 2024.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-25
DOI
https://doi.org/10.5281/zenodo.13312552
Primary Topic
Domain Adaptation and Few-Shot Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Supplementary Material for Retro-Li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization

Zenodo (CERN European Organization for Nuclear Research)
Domain Adaptation and Few-Shot Learning
article

Supplementary Material for Retro-Li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization

article en

Abstract

This is the supplementary material of the paper accepted with the same title in the 27th European Conference on Artificial Intelligence (ECAI), 2024.

Zenodo (CERN European Organization for Nuclear Research)
ETH Zurich (CH), IBM Research - Zurich (CH)
Openalex Percentile: Top 68%
Domain Adaptation and Few-Shot Learning
DOIOpen Access PDFOpenAlex
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Supplementary Material for Retro-Li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS