Papers by Vasu Jindal

2 papers
Bridging the Embodiment Gap in Agricultural Knowledge Representation for Language Models (2025.acl-srw)

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Challenge: a paper quantifies the “embodiment gap” between disembodied language models and embodied agricultural knowledge communication . agronomists and researchers examined the embodiment gap in 78 farmers .
Approach: They propose a framework that integrates linguistic patterns from five domains of agricultural expertise and a new metric for evaluating embodied knowledge representation in language models.
Outcome: The proposed frameworks reduce the embodiment gap by 47.3% across agricultural domains . the proposed framework improves tool usage discourse and soil assessment terminology .
Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks (N18-4)

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Challenge: Existing studies on image caption generation in English focus on Western languages, ignoring Semitic and Middle-Eastern languages like Arabic, Hebrew, Urdu and Persian.
Approach: They propose to leverage the critical dependency of Arabic to generate Arabic captions using root-word based Recurrent Neural Network and Deep Neural networks.
Outcome: The proposed model outperforms English-Arabic translated captions on a dataset from newspapers in the Middle East.

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