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Register a new userFUDGE: Controlled Text Generation With Future Discriminators
الهراء: توليد النص الذي يتم التحكم فيه مع التمييز في المستقبل
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نقترح على التمييز المستقبلي لتوليد (Fudge)، وسيلة مرنة وحيونية للجيل المسيطر الذي يتم التحكم فيه.بالنظر إلى نموذج G موجه مسبقا لتوليد النص من توزيع الفائدة، يتيح الافعال تكييف السمة المرغوبة A (على سبيل المثال، الشكلية) أثناء الوصول إلى تسجيل الدخول فقط إلى سجل الإخراج G فقط.تتعلم Fudge مؤشر سمة يعمل على تسلسل جزئي، ويستخدم مخرجات هذا المؤشر لضبط الاحتمالات الأصلية G.نظهر أن نماذج الهرج تطل على تحلل بايزي للتوزيع الشرطي ل G معين من السمة A.علاوة على ذلك، يمكن أن يؤدي fudge بسهولة تنبؤات للسمات المتعددة المرغوبة.نقوم بتقييم الهراء في ثلاث مهام --- الانتهاء من الإكمال في الشعر، والتحكم في الموضوع في توليد اللغة، وتغيير الشكليات في الترجمة الآلية - - ومراقبة المكاسب في جميع المهام الثلاث.
We propose Future Discriminators for Generation (FUDGE), a flexible and modular method for controlled text generation. Given a pre-existing model G for generating text from a distribution of interest, FUDGE enables conditioning on a desired attribute a (for example, formality) while requiring access only to G's output logits. FUDGE learns an attribute predictor operating on a partial sequence, and uses this predictor's outputs to adjust G's original probabilities. We show that FUDGE models terms corresponding to a Bayesian decomposition of the conditional distribution of G given attribute a. Moreover, FUDGE can easily compose predictors for multiple desired attributes. We evaluate FUDGE on three tasks --- couplet completion in poetry, topic control in language generation, and formality change in machine translation --- and observe gains in all three tasks.
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