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Found 4 papers, 4 papers with code
TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings
The goal of text style transfer is to transform the style of texts while preserving their original meaning, often with only a few examples of the target style.
Learning to Follow Object-Centric Image Editing Instructions Faithfully
Current approaches focusing on image editing with natural language instructions rely on automatically generated paired data, which, as shown in our investigation, is noisy and sometimes nonsensical, exacerbating the above issues.
CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeech
We generate counterspeech using three datasets and observe significant improvement across different attribute scores.
Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models
We describe our system entry for the WASSA 2021 Shared Task (for both Track-1 and Track-2), where we leveraged the information from Pre-trained language models for Track-specific Tasks.
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