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Comment Generation

Article commenting poses new challenges for machines, as it involves multiple cognitive abilities: understanding the given article, formulating opinions and arguments, and organizing natu ral language for expression.

Papers

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Showing 51–65 of 65 papers

TitleStatusHype
DiffuCom: A novel diffusion model for comment generation—0
DCA: Diversified Co-Attention towards Informative Live Video Commenting—0
Energy-bounded Learning for Robust Models of Code—0
Error syntax aware augmentation of feedback comment generation dataset—0
Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation—0
Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection—0
Generating Pertinent and Diversified Comments with Topic-aware Pointer-Generator Networks—0
LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition—0
Learning Comment Generation by Leveraging User-Generated Data—0
InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees—0
Learning to Encode Evolutionary Knowledge for Automatic Commenting Long Novels—0
Learning to Generate Code Comments from Class Hierarchies—0
Learning to Represent Programs with Heterogeneous Graphs—0
LiveChat: Video Comment Generation from Audio-Visual Multimodal Contexts—0
Live Video Comment Generation Based on Surrounding Frames and Live Comments—0
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