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Title:           Measuring Text-Image Retrieval Fairness with Synthetic Data
Subject:         -  Information systems  ->  Information retrieval.Image search.Test collections.-  Social and professional topics  ->  Race and ethnicity.Gender.
Keywords:        Text-Image Retrieval, Fairness, Synthetic Dataset, CLIP
Author:          Lluis Gomez
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     Item: 
      Title: Abstract
     Item: 
      Title: 1 Introduction
     Item: 
      Title: 2 Related Work
     Item: 
      Title: 3 Social bias assessment in text-image retrieval
     Item: 
      Title: 4 SISPI Dataset
     Item: 
      Title: 5 Experiments
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       Item: 
        Title: 5.1 Comparing fairness of CLIP-based models
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        Title: 5.2 Comparing fairness of state-of-the-art text-image retrieval models
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      Title: 6 Discussion
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      Title: 7 Ethical Considerations
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      Title: 8 Conclusions
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      Title: Acknowledgments
     Item: 
      Title: References
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               <rdf:li xml:lang="en">-  Information systems  -&gt;  Information retrieval.Image search.Test collections.-  Social and professional topics  -&gt;  Race and ethnicity.Gender.</rdf:li>
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   Type: CRC32
  Checksum: 06fa5b5d98f14cccb083b00876fae848
   Type: MD5
  Checksum: 491b1a2e6730078ce75e030493e57ab6a5e9c744
   Type: SHA-1
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   Type: SHA-256