Papers by Anas Khan
Hope ‘The Paragraph Guy’ explains the rest : Introducing MeSum, the Meme Summarizer (2024.findings-emnlp)
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| Challenge: | a lack of large datasets for supervised learning and resource-intensive vision language models have hindered the development of meme comprehension. |
| Approach: | They propose a framework to bridge the gap between meme comprehension and vision language models by using a multimodal dataset. |
| Outcome: | The proposed framework outperforms existing methods in the meme comprehension test. |
Sem-DPO: Mitigating Semantic Inconsistency in Preference Optimization for Prompt Engineering (2026.findings-acl)
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Anas Mohamed, Azal Ahmad Khan, Xinran Wang, Ahmad Faraz Khan, Shuwen Ge, Saman Bahzad Khan, Ayaan Ahmad, Ali Anwar
| Challenge: | Direct Preference Optimization (DPO) is an off-policy alternative to RL for automatic prompt engineering, but its token-level regularization leaves semantic inconsistency unchecked as prompts that win higher preference scores can still drift away from the user’s intended meaning. |
| Approach: | They propose a variant of Direct Preference Optimization that preserves semantic consistency while maintaining its simplicity and efficiency. |
| Outcome: | The proposed model outperforms state-of-the-art prompt optimization baselines and several DPO variants on three standard text-to-image prompt-optimization benchmarks and three language models. |