Search for: All records

Learning high-level representations for graphs is crucial for tasks like node classification, where graph pooling aggregates node features to provide a holistic view that enhances predictive performance. Despite numerous methods that have been proposed in this promising and rapidly developing research field, most efforts to generalize the pooling operation to graphs are primarily performance-driven, with fairness issues largely overlooked: i) the process of graph pooling could exacerbate disparities in distribution among various subgroups; ii) the resultant graph structure augmentation may inadvertently strengthen intra-group connectivity, leading to unintended inter-group isolation. To this end, this paper extends the initial effort on fair graph pooling to the development of fair graph neural networks, while also providing a unified framework to collectively address group and individual graph fairness. Our experimental evaluations on multiple datasets demonstrate that the proposed method not only outperforms state-of-the-art baselines in terms of fairness but also achieves comparable predictive performance. 

Developing software projects that incorporate multiple languages has been a prevalent practice for many years. However, the issues encountered by developers during the development process, the underlying challenges causing these issues, and the solutions provided to developers remain unknown. In this paper, our objective is to provide answers to these questions by conducting a study on developer discussions on Stack Overflow (SO). Through a manual analysis of 586 highly relevant posts spanning 14 years, we revealed that multilingual development is a highly and sustainably active topic on SO, with older questions becoming inactive and newer ones getting first asked (and then mostly remaining active for more than one year). From these posts, we observed a diverse array of issues (11 categories), primarily centered around interfacing and data handling across different languages. Our analysis suggests that error/exception handling issues were the most difficult to resolve among those issue categories, while security related issues were most likely to receive an accepted answer. The primary challenge faced by developers was the complexity and diversity inherent in building multilingual code and ensuring interoperability. Additionally, developers often struggled due to a lack of technical expertise on the varied features of different programming languages (e.g., threading and memory management mechanisms). In addition, properly handling message passing across languages constituted a key challenge with using implicit language interfacing. Notably, Stack Overflow emerged as a crucial source of solutions to these challenges, with the majority (73%) of the posts receiving accepted answers, most within a week (36.5% within 24 hours and 25% in the following six days). Based on our analysis results, we have formulated actionable insights and recommendations that can be utilized by researchers and developers in this field.