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Register a new userMultilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
متعددة اللغات متعددة الوسائط التدريبية للتحويل الصفر - نقل عبر اللغات من نماذج لغة الرؤية
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تقوم هذه الدراسات الورقية بالتحويل عبر اللغات الصفرية إلى نماذج لغة الرؤية. على وجه التحديد، نركز على البحث عن نص متعدد اللغات والفيديو واقتراح نموذجا يستند إلى المحولات التي تتعلم أن تضمينات السياق متعددة اللغات متعددة اللغات. تحت إعداد طلقة صفرية، نوضح تجريبيا أن الأداء يتحلل بشكل كبير عند الاستعلام عن نموذج الفيديو النصي متعدد اللغات مع جمل غير إنجليزية. لمعالجة هذه المشكلة، نقدم استراتيجية متعددة الاستخدامات متعددة الاستخدامات متعددة اللغات، وجمع مجموعة بيانات تعليمية متعددة اللغات متعددة اللغات (متعدد HOWTO100M) للتدريب المسبق. تشير التجارب في VTT إلى أن طريقتنا تعمل بشكل كبير على تحسين البحث عن الفيديو في اللغات غير الإنجليزية دون شروح إضافية. علاوة على ذلك، عند توفر التعليقات التوضيحية متعددة اللغات، تتفوقت طريقة لدينا على خطوط الأساس الحديثة بواسطة هامش كبير في البحث عن نص متعدد اللغات للفيديو على VTT و Vatex؛ وكذلك في البحث النص متعدد اللغات إلى الصورة على multi30k. يتوفر نموذجنا ومتعدد HOWTO100M على http://github.com/berniebear/multi-ht100m.
This paper studies zero-shot cross-lingual transfer of vision-language models. Specifically, we focus on multilingual text-to-video search and propose a Transformer-based model that learns contextual multilingual multimodal embeddings. Under a zero-shot setting, we empirically demonstrate that performance degrades significantly when we query the multilingual text-video model with non-English sentences. To address this problem, we introduce a multilingual multimodal pre-training strategy, and collect a new multilingual instructional video dataset (Multi-HowTo100M) for pre-training. Experiments on VTT show that our method significantly improves video search in non-English languages without additional annotations. Furthermore, when multilingual annotations are available, our method outperforms recent baselines by a large margin in multilingual text-to-video search on VTT and VATEX; as well as in multilingual text-to-image search on Multi30K. Our model and Multi-HowTo100M is available at http://github.com/berniebear/Multi-HT100M.
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