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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 1–50 of 65 papers

TitleStatusHype
InCoder: A Generative Model for Code Infilling and SynthesisCode2
Prompting for Numerical Sequences: A Case Study on Market Comment GenerationCode2
CoNT: Contrastive Neural Text GenerationCode2
Retrieve and Refine: Exemplar-based Neural Comment GenerationCode1
Automating Code Review Activities by Large-Scale Pre-trainingCode1
Impact of Evaluation Methodologies on Code SummarizationCode1
Knowledge Enhanced Model for Live Video Comment GenerationCode0
Automatic Generation of Personalized Comment Based on User ProfileCode0
MESIA: Understanding and Leveraging Supplementary Nature of Method-level Comments for Automatic Comment GenerationCode0
A variational selection mechanism for article comment generationCode0
Code Attention: Translating Code to Comments by Exploiting Domain FeaturesCode0
StoryER: Automatic Story Evaluation via Ranking, Rating and ReasoningCode0
Enhancing Code Generation via Bidirectional Comment-Level Mutual GroundingCode0
Learning with Contrastive Examples for Data-to-Text GenerationCode0
Leveraging Reward Models for Guiding Code Review Comment GenerationCode0
Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence ModelCode0
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection ModelsCode0
Automatic Comment Generation via Multi-Pass DeliberationCode0
Exploring Methods for Generating Feedback Comments for Writing LearningCode0
Automated Medical Report Generation for ECG Data: Bridging Medical Text and Signal Processing with Deep LearningCode0
Cross-Modal Commentator: Automatic Machine Commenting Based on Cross-Modal InformationCode0
One Comment from One Perspective: An Effective Strategy for Enhancing Automatic Music CommentCode0
Investigating the Efficacy of Large Language Models for Code Clone DetectionCode0
Market Comment Generation from Data with Noisy Alignments—0
Mimicking the Familiar: Dynamic Command Generation for Information Theft Attacks in LLM Tool-Learning System—0
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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