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This paper presents an open-source re-implementation of the NAVER LABS instruction-following pipeline for IWSLT 2026, using SeamlessM4T-v2-large and Qwen3-4B-Instruct, with 100k synthetic examples.
This paper describes NAVER LABS Europe's submission to the IWSLT 2026 instruction-following short track, improving upon their previous winning system by using a new speech projector (SpeechMapper) trained solely on ASR data and augmenting training with a synthetic SQA dataset (fakACL). The resulting system ties for first place in the constrained track while using a weaker LLM backbone.
This paper describes the MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task, using Parakeet and Qwen 3.5 models with adaptive 'black-box' policies and a RAG mechanism for context, achieving significant quality improvements.