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Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning

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Published in:Journal of Computational Vision and Imaging Systems
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Computational Vision and Imaging Systems
description
discipline_display Computer Science
discipline_facet Computer Science
format Online Article
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genre Journal Article
id rss_article:78501
institution FRELIP
journal_source_facet Journal of Computational Vision and Imaging Systems
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
Computer Science
General
Computer Science
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Science
General
Computer Science
Computer Science
General
Computer Science
subject_facet Computer Science
General
Computer Science
title Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_auth Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_full Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_fullStr Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_full_unstemmed Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_short Explainable Chain-of-Thought Object Counting in Vision-Language Models using Reinforcement Learning
title_sort explainable chain-of-thought object counting in vision-language models using reinforcement learning
topic Computer Science
General
Computer Science
url https://openjournals.uwaterloo.ca/index.php/vsl/article/view/7124