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The Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice Question Answering (MCQA) across 21 languages, is detailed, which involves multilingual Multiple-Choice Question Answering across 21 languages.
This work empirically diagnose the root cause across six per-layer methods and three speech-LLM architectures and proposes a two-pool allocation that normalises encoder and LLM parameters into independent pools, and shows that joint $\ell_2$ sensitivity and the original $(\varepsilon,\delta)$-DP guarantee are unchanged.
