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Ahmed El-Kishky

4 accepted papers

2023

Simple Temporal Adaptation to Changing Label Sets: Hashtag Prediction via Dense KNN

Niloofar Mireshghallah, Nikolai Vogler, Junxian He, Omar Florez, Ahmed El-Kishky, Taylor Berg-Kirkpatrick
EMNLP 2023short main

User-generated social media data is constantly changing as new trends influence online discussion and personal information is deleted due to privacy concerns. However, traditional NLP models rely on fixed training datasets, which means they are unable to adapt to temporal change---both test distribu…

Cited by 0Source ↗Scholar ↗
2021

Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data

Wei-Jen Ko, Ahmed El-Kishky, Adithya Renduchintala, Vishrav Chaudhary, Naman Goyal, Francisco Guzmán +3
ACL 2021long

The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are linguistically related or similar to high-resource languages; these related languages may share many lexical or syntactic s…

Cited by 44Source ↗PDF ↗code ↗Scholar ↗
2021

Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications

Shuo Sun, Ahmed El-Kishky, Vishrav Chaudhary, James Cross, Lucia Specia, Francisco Guzmán
EMNLP 2021main

Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson correlation with human labels. Recent QE models have achieved previously-unseen levels of correlation with human judgments…

Cited by 3Source ↗PDF ↗Scholar ↗
2021

XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment

Ahmed El-Kishky, Adithya Renduchintala, James Cross, Francisco Guzmán, Philipp Koehn
EMNLP 2021main

Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such as machine translation and cross-lingual wikification. While knowledge bases contain a large number of entities in high-resource languages such as English and French, corresponding entities for lower-resource…

Cited by 14Source ↗PDF ↗Scholar ↗