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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 26–50 of 65 papers

TitleStatusHype
MOPRD: A multidisciplinary open peer review dataset—0
Multi-Attribute Controlled Text Generation with Contrastive-Generator and External-Discriminator—0
OMPGPT: A Generative Pre-trained Transformer Model for OpenMP—0
Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation—0
Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation—0
Read, Attend and Comment: A Deep Architecture for Automatic NewsComment Generation—0
ReviewAgents: Bridging the Gap Between Human and AI-Generated Paper Reviews—0
Sentence-level Feedback Generation for English Language Learners: Does Data Augmentation Help?—0
Shared Task on Feedback Comment Generation for Language Learners—0
Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation—0
TAG : Type Auxiliary Guiding for Code Comment Generation—0
Topic Analysis for Text with Side Data—0
Toward a Task of Feedback Comment Generation for Writing Learning—0
Toward Imitating Visual Attention of Experts in Software Development Tasks—0
Towards Context-Aware Code Comment Generation—0
Towards Controlled and Diverse Generation of Article Comments—0
API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations—0
ViCo: Engaging Video Comment Generation with Human Preference Rewards—0
APIContext2Com: Code Comment Generation by Incorporating Pre-Defined API Documentation—0
Automatic Article Commenting: the Task and Dataset—0
Automatic Generation of News Comments Based on Gated Attention Neural Networks—0
Automating Horizon Scanning in Future Studies—0
Creating Corpora for Research in Feedback Comment Generation—0
DeepCodeProbe: Towards Understanding What Models Trained on Code Learn—0
DeepCRCEval: Revisiting the Evaluation of Code Review Comment Generation—0
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