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Task-Preserving Multilingual Instruction Tuning for Open-Ended QA in WMT 2026 MIST

Paper recorded by Signals 4 on 2026-10-21 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-21 on arXiv · recorded by Signals 4 on 2026-10-22

Category: cs.CL · 自然语言处理 · first seen 2026-10-22

Abstract

This paper describes our submission to the WMT 2026 Multilingual Instruction Shared Task. We adapt Qwen3-8B with LoRA using organiser-provided data, EuroAlpaca, a multilingual instruction dataset created through task-preserving localisation, and CrossEuroAlpaca, a cross-lingual augmentation that assigns different source and target languages to instructions, contexts and responses. Our system targe

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#189 most recent of 660 cs.CL papers we have recorded · ↑ newer: Your Benchmark Is an Empirical Measure Over Difficulty · ↓ older: NarraSpace: Multimodal Scene-Grounded Evidence for Picture-Description
Cite this page: Task-Preserving Multilingual Instruction Tuning for Open-Ended QA in WMT 2026 MIST: the #189 most recent of 660 cs.CL papers we have recorded (as of 2026-10-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/task-preserving-multilingual-instruction-tuning-for-open-ended-qa-in-wmt-2026-mi.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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