Papers by Christine Basta

2 papers
Evaluating Gender Bias in Speech Translation (2022.lrec-1)

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Challenge: Existing evaluation techniques for gender biases are lacking in the field of machine translation.
Approach: They propose to use a free evaluation set to evaluate gender bias in speech translation.
Outcome: The proposed set is the speech version of WinoMT, an MT challenge set.
Enhancing Software Requirements Engineering with Language Models and Prompting Techniques: Insights from the Current Research and Future Directions (2025.acl-srw)

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Challenge: Large Language Models (LLMs) offer transformative potential for Software Requirements Engineering (SRE), but they face challenges such as domain ignorance, hallucinations, and high computational costs.
Approach: They propose a conceptual framework that integrates Small Language Models and Knowledge-Augmented LMs with LangChain to address these limitations systematically.
Outcome: The proposed framework addresses six technical challenges and two research gaps through a systematic review of LLM applications in software requirements engineering.

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