Related papers: Automating App Review Response Generation
Mobile apps are becoming an integral part of people's daily life by providing various functionalities, such as messaging and gaming. App developers try their best to ensure user experience during app development and maintenance to improve…
Previous studies have demonstrated that proactive interaction with user reviews has a positive impact on the perception of app users and encourages them to submit revised ratings. Nevertheless, developers encounter challenges in managing a…
Recent studies showed that the dialogs between app developers and app users on app stores are important to increase user satisfaction and app's overall ratings. However, the large volume of reviews and the limitation of resources discourage…
User experience of mobile apps is an essential ingredient that can influence the audience volumes and app revenue. To ensure good user experience and assist app development, several prior studies resort to analysis of app reviews, a type of…
Studies show that developers' answers to the mobile app users' feedbacks on app stores can increase the apps' star rating. To help app developers generate answers that are related to the users' issues, recent studies develop models to…
Responding to user reviews promptly and satisfactorily improves application ratings, which is key to application popularity and success. The proliferation of such reviews makes it virtually impossible for developers to keep up with…
Automated code review comment generation (RCG) aims to assist developers by automatically producing natural language feedback for code changes. Existing approaches are primarily either generation-based, using pretrained language models, or…
Reviews contain rich information about product characteristics and user interests and thus are commonly used to boost recommender system performance. Specifically, previous work show that jointly learning to perform review generation…
The users often have many product-related questions before they make a purchase decision in E-commerce. However, it is often time-consuming to examine each user review to identify the desired information. In this paper, we propose a novel…
The number of applications in Google Play has increased dramatically in recent years. On Google Play, users can write detailed reviews and rate apps, with these ratings significantly influencing app success and download numbers. Reviews…
In this paper, we propose a novel model RevGAN that automatically generates controllable and personalized user reviews based on the arbitrarily given sentimental and stylistic information. RevGAN utilizes the combination of three novel…
Reward modeling is crucial for aligning large language models (LLMs) with human preferences, especially in reinforcement learning from human feedback (RLHF). However, current reward models mainly produce scalar scores and struggle to…
User reviews on e-commerce and review sites are crucial for making purchase decisions, although creating detailed reviews is time-consuming and labor-intensive. In this study, we propose a novel use of dialogue systems to facilitate user…
This research presents and compares multiple approaches to automate the generation of literature reviews using several Natural Language Processing (NLP) techniques and retrieval-augmented generation (RAG) with a Large Language Model (LLM).…
The use of large language models like ChatGPT in code review offers promising efficiency gains but also raises concerns about correctness and safety. Existing evaluation methods for code review generation either rely on automatic…
Retrieval-augmented generation (RAG) is a popular technique for using large language models (LLMs) to build customer-support, question-answering solutions. In this paper, we share our team's practical experience building and maintaining…
Online reviews provide rich information about products and service, while it remains inefficient for potential consumers to exploit the reviews for fulfilling their specific information need. We propose to explore question generation as a…
The energy inefficiency of the apps can be a major issue for the app users which is discussed on App Stores extensively. Previous research has shown the importance of investigating the energy related app reviews to identify the major causes…
Thanks to unprecedented language understanding and generation capabilities of large language model (LLM), Retrieval-augmented Code Generation (RaCG) has recently been widely utilized among software developers. While this has increased…
To assist human review process, we build a novel ReviewRobot to automatically assign a review score and write comments for multiple categories such as novelty and meaningful comparison. A good review needs to be knowledgeable, namely that…