Author

John D. Kelleher

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Review Open access Jul 2026

A survey of gender bias mitigation in neural machine translation

Transformer-based models are the current state-of-the-art in machine translation (MT) research. These systems can generate fluent and contextually appropriate translations for many translation tasks and languages. These models are trained on large amounts of unlabelled data, often consisting of billions of examples, an...

Neha Gajakos, Christopher Staff, Brenda Murphy et al. · Language Resources and Evalu... · 0 citations

#natural language process... Review Feb 2026

Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey

This survey provides a systematic analysis of multi-LLM routing and cascading approaches, focusing on systems that route queries across a pool of independently trained LLMs at inference time, and demonstrates that effective multi-LLM routing requires balancing competing objectives.

Yasmin Moslem, John D. Kelleher · arXiv.org · 21 citations · ⚡1