Papers Comment Generation
“Comment Generation” 태그가 달린 논문 65편 · 필터 해제
Sentence-level Feedback Generation for English Language Learners: Does Data Augmentation Help?
In this paper, we present strong baselines for the task of Feedback Comment Generation for Writing Learning. Given a sentence and an error span, the task is to generate a feedback comment explaining the error. Sentences …
Comment GenerationData AugmentationSentenceMOPRD: A multidisciplinary open peer review dataset
Open peer review is a growing trend in academic publications. Public access to peer review data can benefit both the academic and publishing communities. It also serves as a great support to studies on review comment gen…
Comment GenerationReview GenerationStoryER: Automatic Story Evaluation via Ranking, Rating and Reasoning
Existing automatic story evaluation methods place a premium on story lexical level coherence, deviating from human preference. We go beyond this limitation by considering a novel \textbf{Story} \textbf{E}valuation method…
Comment GenerationDecoderMulti-Attribute Controlled Text Generation with Contrastive-Generator and External-Discriminator
Though existing researches have achieved impressive results in controlled text generation, they focus mainly on single-attribute control. However, in applications like automatic comments, the topic and sentiment need to …
AttributeComment GenerationText GenerationAutomatic Comment Generation via Multi-Pass Deliberation
Deliberation is a common and natural behavior in human daily life. For example, when writing papers or articles, we usually first write drafts, and then iteratively polish them until satisfied. In light of such a human c…
ArticlesComment GenerationAutomating Horizon Scanning in Future Studies
We introduce document retrieval and comment generation tasks for automating horizon scanning. This is an important task in the field of futurology that collects sufficient information for predicting drastic societal chan…
ArticlesComment GenerationRetrievalCoNT: Contrastive Neural Text Generation
Recently, contrastive learning attracts increasing interests in neural text generation as a new solution to alleviate the exposure bias problem. It introduces a sequence-level training signal which is crucial to generati…
Code Comment GenerationComment GenerationContrastive LearningData-to-Text Generation+3InCoder: A Generative Model for Code Infilling and Synthesis
Code is seldom written in a single left-to-right pass and is instead repeatedly edited and refined. We introduce InCoder, a unified generative model that can perform program synthesis (via left-to-right generation) as we…
Code GenerationComment GenerationProgram SynthesisLAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition
Code comment generation is the task of generating a high-level natural language description for a given code method or function. Although researchers have been studying multiple ways to generate code comments automatical…
Code Comment GenerationComment GenerationLanguage ModelingLanguage Modelling+3Automating Code Review Activities by Large-Scale Pre-training
Code review is an essential part to software development lifecycle since it aims at guaranteeing the quality of codes. Modern code review activities necessitate developers viewing, understanding and even running the prog…
Comment GenerationTopic Analysis for Text with Side Data
Although latent factor models (e.g., matrix factorization) obtain good performance in predictions, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendations. In this paper, …
Comment GenerationEnergy-bounded Learning for Robust Models of Code
In programming, learning code representations has a variety of applications, including code classification, code search, comment generation, bug prediction, and so on. Various representations of code in terms of tokens, …
Code ClassificationCode SearchComment GenerationOut of Distribution (OOD) DetectionExploring Methods for Generating Feedback Comments for Writing Learning
The task of generating explanatory notes for language learners is known as feedback comment generation. Although various generation techniques are available, little is known about which methods are appropriate for this t…
Comment GenerationRetrievalImpact of Evaluation Methodologies on Code Summarization
There has been a growing interest in developing machine learning (ML) models for code summarization tasks, e.g., comment generation and method naming. Despite substantial increase in the effectiveness of ML models, the e…
Code SummarizationComment GenerationShared Task on Feedback Comment Generation for Language Learners
In this paper, we propose a generation challenge called Feedback comment generation for language learners. It is a task where given a text and a span, a system generates, for the span, an explanatory note that helps the …
Comment GenerationTowards Controlled and Diverse Generation of Article Comments
Much research in recent years has focused on automatic article commenting. However, few of previous studies focus on the controllable generation of comments. Besides, they tend to generate dull and commonplace comments, …
ArticlesComment GenerationDecoderDiversity+1Learning to Generate Code Comments from Class Hierarchies
Descriptive code comments are essential for supporting code comprehension and maintenance. We propose the task of automatically generating comments for overriding methods. We formulate a novel framework which accommodate…
Comment GenerationDescriptiveSpecificityAPI2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations
Code comments can help in program comprehension and are considered as important artifacts to help developers in software maintenance. However, the comments are mostly missing or are outdated, specially in complex softwar…
Comment GenerationMachine TranslationGenerating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection
Automatic comment generation is a special and challenging task to verify the model ability on news content comprehension and language generation. Comments not only convey salient and interesting information in news artic…
ArticlesClusteringComment GenerationDecoder+3InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees
Building deep learning models on source code has found many successful software engineering applications, such as code search, code comment generation, bug detection, code migration, and so on. Current learning technique…
Clone DetectionCode ClassificationCode Comment GenerationCode Search+5