相关论文: Supporting the Task-driven Skill Identification in…

Open source software projects usually acknowledge contributions with text files, websites, and other idiosyncratic methods. These data sources are hard to mine, which is why contributorship is most frequently measured through changes to…

Textual label names (descriptions) are typically semantically rich in many natural language understanding (NLU) tasks. In this paper, we incorporate the prompting methodology, which is widely used to enrich model input, into the label side…

Labels on platforms such as GitHub support triage and coordination, yet little is known about how well they align with code modifications or how such alignment affects collaboration across contributor experience levels. We present a case…

With the increasing popularity of online learning, intelligent tutoring systems are regaining increased attention. In this paper, we introduce adaptive algorithms for personalized assignment of learning tasks to student so that to improve…

Word representation is a key component in neural-network-based sequence labeling systems. However, representations of unseen or rare words trained on the end task are usually poor for appreciable performance. This is commonly referred to as…

The current study proposes an innovative methodology for the profiling of psychological traits of Operations Management (OM) and Supply Chain Management (SCM) professionals. We use innovative methods and tools of text mining and social…

Machine learning-based techniques open up many opportunities and improvements to derive deeper and more practical insights from data that can help businesses make informed decisions. However, the majority of these techniques focus on the…

In recent years, open-source software (OSS) has become increasingly prevalent in developing software products. While OSS documentation is the primary source of information provided by the developers' community about a product, its role in…

Several studies have evaluated automatic techniques for classifying software issue reports to assist practitioners in effectively assigning relevant resources based on the type of issue. Currently, no comprehensive overview of this area has…

As open source software (OSS) becomes increasingly mature and popular, there are significant challenges with properly accounting for usability concerns for the diverse end users. Participatory design, where multiple stakeholders collaborate…

Usability and user experience (UX) issues are often not well emphasized and addressed in open source software (OSS) development. There is an imperative need for supporting OSS communities to collaboratively identify, understand, and fix UX…

Open Source Software (OSS) development challenges traditional software engineering practices. In particular, OSS projects are managed by a large number of volunteers, working freely on the tasks they choose to undertake. OSS projects also…

Supervised learning, especially supervised deep learning, requires large amounts of labeled data. One approach to collect large amounts of labeled data is by using a crowdsourcing platform where numerous workers perform the annotation…

The sustainability of open source software (OSS) projects hinges on contributor retention. Interpersonal challenges can inhibit a feeling of welcomeness among contributors, particularly from underrepresented groups, which impacts their…

Crowdsourcing systems, in which numerous tasks are electronically distributed to numerous "information piece-workers", have emerged as an effective paradigm for human-powered solving of large scale problems in domains such as image…

We propose a formal definition for the task of suggestion mining in the context of a wide range of open domain applications. Human perception of the term \emph{suggestion} is subjective and this effects the preparation of hand labeled…

Scalable oversight studies methods of training and evaluating AI systems in domains where human judgment is unreliable or expensive, such as scientific research and software engineering in complex codebases. Most work in this area has…

Open source software (OSS) projects rely on complex networks of contributors whose interactions drive innovation and sustainability. This study presents a comprehensive analysis of OSS contributor networks using advanced graph neural…

Frame semantic parsing is an important component of task-oriented dialogue systems. Current models rely on a significant amount training data to successfully identify the intent and slots in the user's input utterance. This creates a…

A central challenge towards developing robots that can relate human language to their perception and actions is the scarcity of natural language annotations in diverse robot datasets. Moreover, robot policies that follow natural language…