Philipp Koehn

Machine translation benchmarks have functionally saturated, but pairing human-authored failure cases with deterministic verification rules reveals critical multimodal blind spots that automated metrics consistently miss.

The curse of multilinguality may not be a fundamental barrier; instead, it’s a byproduct of data and training practices.

Emotion-sensitive neurons in LALMs are language-specific, but pooling cross-lingual evidence reveals powerful, transferable Multilingual Emotion Neurons that enhance affective control.

Injecting targeted language features at inference time can boost multilingual model performance by over 10 percentage points without retraining.

Finally, voice anonymization offers a smooth, tunable knob to balance privacy and prosody, instead of forcing you to pick just one.