Papers by Omar Khan

2 papers
Learning to Retrieve Engaging Follow-Up Queries (2023.findings-eacl)

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Challenge: Open domain conversational agents can answer a wide range of targeted queries, but knowledge exploration is a lengthy task.
Approach: They propose a retrieval based system for predicting the next questions that the user might have . they train ranking models on a dataset called the Follow-up Query Bank .
Outcome: The proposed system can proactively assist users in knowledge exploration leading to a more engaging dialog.
KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding (2025.findings-acl)

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Challenge: Optical Character Recognition (OCR) is a key component of document processing . Arabic text recognition has complex typographic and calligraphic features .
Approach: They propose a comprehensive Arabic OCR benchmark that fills the gaps in evaluation systems.
Outcome: The proposed benchmark outperforms existing models in Arabic by 60% in the character error rate . the best model achieves only 65% accuracy in PDF-to-Markdown conversion .

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