mlsanityData to 14 Oct 2026

NAVER LABS System Re-implementation for the IWSLT 2026 Instruction-Following Task

arXiv 2607.05623 ↗First posted 6 Jul 2026cs.CLcited by 0

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Abstract (arXiv)

We re-implement the NAVER LABS IWSLT 2025 instruction-following pipeline for the IWSLT 2026 Shared Task (constrained condition, short audio track), adapting it to the mandated components: SeamlessM4T-v2-large as the speech encoder and Qwen3-4B-Instruct as the LLM backbone. The three-stage approach projector alignment, text-only LoRA pre-training, and multimodal merging is preserved from the original design. We additionally construct 100k synthetic instruction-following examples across ten speech-centric task types (10k per task) from the provided corpora, suitable for further Stage 3 fine-tuning. Our primary model achieves COMET 0.781 on EN-ZH speech translation and BERTScore-F1 0.346 on English SQA on the MCIF benchmark.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 23 references that are in the map. First posted on arXiv 6 Jul 2026.

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References · 10

  1. 2017Attention Is All You Needcited by 60,361
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2024The Llama 3 Herd of Modelscited by 14,715
  4. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  5. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  6. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  7. 2020COMET: A Neural Framework for MT Evaluationcited by 1,033
  8. 2023Prometheus: Inducing Fine-grained Evaluation Capability in Language Modelscited by 575
  9. 2023SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilitiescited by 529
  10. 2025NAVER LABS Europe Submission to the Instruction-following Trackcited by 5

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