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A Toolbox for Improving Evolutionary Prompt Search
Daniel Grießhaber, Maximilian Kimmich, Johannes Maucher +1
Evolutionary prompt optimization has demonstrated effectiveness in refining prompts for LLMs. However, existing approaches lack robust operators and efficient evaluation mechanisms…
The Impact of Code-switched Synthetic Data Quality is Task Dependent: Insights from MT and ASR
Injy Hamed, Ngoc Thang Vu, Nizar Habash
Code-switching, the act of alternating between languages, emerged as a prevalent global phenomenon that needs to be addressed for building user-friendly language technologies. A ma…
A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions
Injy Hamed, Caroline Sabty, Slim Abdennadher +3
Language in the Arab world presents a complex diglossic and multilingual setting, involving the use of Modern Standard Arabic, various dialects and sub-dialects, as well as multipl…
Towards Zero-Shot, Controllable Dialog Planning with LLMs
Dirk Väth, Ngoc Thang Vu
Recently, Large Language Models (LLMs) have emerged as an alternative to training task-specific dialog agents, due to their broad reasoning capabilities and performance in zero-sho…
Data Augmentation Techniques for Machine Translation of Code-Switched Texts: A Comparative Study
Injy Hamed, Nizar Habash, Ngoc Thang Vu
Code-switching (CSW) text generation has been receiving increasing attention as a solution to address data scarcity. In light of this growing interest, we need more comprehensive s…