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Measure how biases in high-resource training languages transfer to low-resource language outputs during multilingual fine-tuning.
Achieve competitive accuracy with 10x reduction in FLOPs for on-device inference through novel quantization and pruning strategies.
Extend fairness metrics to handle intersectional protected groups without exponential sample size requirements.
Build a system that discovers new adversarial attack categories autonomously, beyond known jailbreak taxonomies.
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