Papers by Kazi Sajeed Mehrab
CoDesc: A Large Code–Description Parallel Dataset (2021.findings-acl)
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Masum Hasan, Tanveer Muttaqueen, Abdullah Al Ishtiaq, Kazi Sajeed Mehrab, Md. Mahim Anjum Haque, Tahmid Hasan, Wasi Ahmad, Anindya Iqbal, Rifat Shahriyar
| Challenge: | Existing models for natural language and programming languages are lagging behind due to a lack of large datasets and benchmarks. |
| Approach: | They present a large parallel dataset of Java methods and natural language descriptions that is used to train deep neural models. |
| Outcome: | The proposed dataset improves code summarization and code search by 22% and opens up possibilities for pretrained language models for Java. |
M3D: MultiModal MultiDocument Fine-Grained Inconsistency Detection (2024.emnlp-main)
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| Challenge: | Existing methods for fact-checking claim are limited by ambiguous information and lack sample-level predictions. |
| Approach: | They propose a method that predicts the logical relationship of each aspect of a claim from a set of multimodal documents. |
| Outcome: | The proposed method outperforms existing models on two benchmarks while providing finer-grained predictions, explanations, and evidence. |