التأطير ينطوي على العرض التقديمي الإيجابي أو السلبي للحجة أو إصدار اعتمادا على جمهور المتكلم والهدف.يمكن أن يكون للاختلافات في تأطير معجمي، محور عملنا، آثار كبيرة على آراء ومعتقدات الشعوب.لإحراز تقدم نحو حجج Reframing للتأثيرات الإيجابية، نقوم بإنشاء مجموعة بيانات وطريقة لهذه المهمة.نحن نستخدم موردا معجميا للدلالات "" لإنشاء كائن متوازي واقتراح طريقة للوقائية التي تجمع بين جيل النص القابل للتحكم (دلالة إيجابية) مع مكون استقصي بعد فك التشفير (نفس الإشارات).تظهر نتائجنا أن طريقتنا فعالة مقارنة مع خطوط الأساس القوية على طول أبعاد الطلاقة والمعنى والجدارة بالثقة / الحد من الخوف.
Framing involves the positive or negative presentation of an argument or issue depending on the audience and goal of the speaker. Differences in lexical framing, the focus of our work, can have large effects on peoples' opinions and beliefs. To make progress towards reframing arguments for positive effects, we create a dataset and method for this task. We use a lexical resource for connotations'' to create a parallel corpus and propose a method for argument reframing that combines controllable text generation (positive connotation) with a post-decoding entailment component (same denotation). Our results show that our method is effective compared to strong baselines along the dimensions of fluency, meaning, and trustworthiness/reduction of fear.
References used
https://aclanthology.org/
To obtain high-quality sentence embeddings from pretrained language models (PLMs), they must either be augmented with additional pretraining objectives or finetuned on a large set of labeled text pairs. While the latter approach typically outperforms
Paraphrase generation has benefited extensively from recent progress in the designing of training objectives and model architectures. However, previous explorations have largely focused on supervised methods, which require a large amount of labeled d
We study the problem of Cross-lingual Event Argument Extraction (CEAE). The task aims to predict argument roles of entity mentions for events in text, whose language is different from the language that a predictive model has been trained on. Previous
We describe our submissions to the 6th edition of the Social Media Mining for Health Applications (SMM4H) shared task. Our team (OGNLP) participated in the sub-task: Classification of tweets self-reporting potential cases of COVID-19 (Task 5). For ou
Taxonomies are symbolic representations of hierarchical relationships between terms or entities. While taxonomies are useful in broad applications, manually updating or maintaining them is labor-intensive and difficult to scale in practice. Conventio