Papers by Jesse Atuhurra
HLU: Human Vs LLM Generated Text Detection Dataset for Urdu at Multiple Granularities (2025.coling-main)
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| Challenge: | Using large language models (LLMs) to generate human-like text has raised concerns about misuse, especially in low-resource languages like Urdu. |
| Approach: | They propose a dataset that contains documents, paragraphs, and sentences . they conducted human evaluations and automated evaluations . |
| Outcome: | The proposed dataset shows that distinguishing between human and machine-generated text is challenging for both humans and LLMs. |
VLURes: Benchmarking Long-Text Grounding and Cross-Lingual Robustness in Vision Language Models (2026.findings-acl)
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| Challenge: | ***VLURes** provides a practical testbed for long-text grounding and multilingual robustness in web-realistic agent settings. |
| Approach: | They propose a multilingual benchmark for evaluating vision-language models under long-text grounding. |
| Outcome: | ***VLURes** provides a testbed for long-text grounding and multilingual robustness in web-realistic agent settings. |