الملخص نقدم إطارا جديدا للملقة، دلالات الحدث العصبي (NES)، لفهم اللغة التركيبية التركيبية.يعامل نهجنا جميع الكلمات كصفوفات مصنوعة من التصنيف لتشكيل عقوبة ذات معنى بضرب درجات الإخراج.تنطبق هذه المصنفات على المناطق المكانية (الأحداث) ويمشر NES هيكلها الدلالي من اللغة عن طريق توجيه الأحداث إلى مدخلات حجة مصنف مختلفة عن طريق الاهتمام الناعم.NES هي نهاية قابلة للتدريب من خلال نزول التدرج مع الحد الأدنى من الإشراف.نقيم طريقةنا على مهام اللغة التركيبية المتراكمة في إعدادات الاصطناعية والواقعية التي تسيطر عليها.توفر NES إمكانية تعميم أقوى من الأطر التركيبية القياسية القائمة على الوظائف، مع تحسين الدقة على الأساليب العصبية الحديثة في مهام اللغة العالمية الحقيقية.
Abstract We present a new conjunctivist framework, neural event semantics (NES), for compositional grounded language understanding. Our approach treats all words as classifiers that compose to form a sentence meaning by multiplying output scores. These classifiers apply to spatial regions (events) and NES derives its semantic structure from language by routing events to different classifier argument inputs via soft attention. NES is trainable end-to-end by gradient descent with minimal supervision. We evaluate our method on compositional grounded language tasks in controlled synthetic and real-world settings. NES offers stronger generalization capability than standard function-based compositional frameworks, while improving accuracy over state-of-the-art neural methods on real-world language tasks.
References used
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