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Nathan Jacobs

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Nathan Jacobs — 30 papers, h 32
  • Nathan Jacobs — 16 papers
  • Nathan Jacobs — 3 papers, h 9
  • Nathan Jacobs — 3 papers
  • Nathan Jacobs — 1 paper
  • Nathan Jacobs — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedConText-CIR: Learning from Concepts in Text for Composed Image Retrieval

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2025

Global and Local Entailment Learning for Natural World Imagery

Srikumar Sastry, Aayush Dhakal, Eric Xing +2

Learning the hierarchical structure of data in vision-language models is a significant challenge. Previous works have attempted to address this challenge by employing entailment le…

cs.CV2025

QuARI: Query Adaptive Retrieval Improvement

Eric Xing, Abby Stylianou, Robert Pless +1

Massive-scale pretraining has made vision-language models increasingly popular for image-to-image and text-to-image retrieval across a broad collection of domains. However, these m…

cs.CV2025★ 1 cited

ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval

Eric Xing, Pranavi Kolouju, Robert Pless +2

Composed image retrieval (CIR) is the task of retrieving a target image specified by a query image and a relative text that describes a semantic modification to the query image. Ex…

cs.CV2025

good4cir: Generating Detailed Synthetic Captions for Composed Image Retrieval

Pranavi Kolouju, Eric Xing, Robert Pless +2

Composed image retrieval (CIR) enables users to search images using a reference image combined with textual modifications. Recent advances in vision-language models have improved C…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.