Related papers: Learning migration models for supporting increment…
Simultaneous machine translation, which aims at a real-time translation, is useful in many live scenarios but very challenging due to the trade-off between accuracy and latency. To achieve the balance for both, the model needs to wait for…
Large language models (LLMs) still struggle across tasks outside of high-resource languages. In this work, we investigate cross-lingual transfer to lower-resource languages where task-specific post-training data is scarce. Building on prior…
Enhancing the adaptive capabilities of large language models is a critical pursuit in both research and application. Traditional fine-tuning methods require substantial data and computational resources, especially for enhancing specific…
Information Retrieval Systems have revolutionized the organization and extraction of Information. In recent years, mobile applications (apps) have become primary tools of collecting and disseminating information. However, limited research…
Industries such as banking, telecom, and airlines - o6en have large so6ware systems that are several decades old. Many of these systems are written in old programming languages such as COBOL, PL/1, Assembler, etc. In many cases, the…
To keep up with constantly growing user demands for services with higher quality and bandwidth requirements, telecommunication operators are forced to upgrade their networks. This upgrade, or migration of the network to a new technology, is…
Fine-tuning pre-trained language models, particularly large language models, demands extensive computing resources and can result in varying performance outcomes across different domains and datasets. This paper examines the approach of…
With multilingual machine translation (MMT) models continuing to grow in size and number of supported languages, it is natural to reuse and upgrade existing models to save computation as data becomes available in more languages. However,…
Developing mobile applications remains difficult, time consuming, and error-prone, in spite of the number of existing platforms and tools. In this paper, we define MoDroid, a high-level modeling language to ease the development of Android…
Modern enterprise computing systems integrate numerous subsystems to resolve a common task by yielding emergent behavior. A widespread approach is using services implemented with Web technologies like REST or OpenAPI, which offer an…
Continuous Integration (CI) is a widely adopted practice for faster code change integration and testing. Developers often migrate between CI systems in pursuit of features like matrix building or better logging. However, this migration is…
Large Language Models (LLMs) remain heavily centered on English, with limited performance in low-resource languages. Existing adaptation approaches, such as continual pre-training, demand significant computational resources. In the case of…
Large Language Models excel in tasks like natural language understanding and text generation. Prompt engineering plays a critical role in leveraging LLM effectively. However, LLMs black-box nature hinders its interpretability and effective…
The migration process between different third-party software libraries is hard, complex and error-prone. Typically, during a library migration process, developers opt to replace methods from the retired library with other methods from a new…
The euphoria around microservices has decreased over the years, but the trend of modernizing legacy systems to this novel architectural style is unbroken to date. A variety of approaches have been proposed in academia and industry, aiming…
Training large language models is a computationally intensive process that often requires substantial resources to achieve state-of-the-art results. Incremental layer-wise training has been proposed as a potential strategy to optimize the…
In recent years, there has been a tremendous interest in using generative AI, and particularly large language models (LLMs) in software engineering; indeed there are now several commercially available tools, and many large companies also…
Moving mission-oriented enterprise applications to cloud environments is a major IT strategic task and requires a systematic approach. The foci of this paper are to review and examine existing cloud migration approaches from the process…
Advances in incremental Datalog evaluation strategies have made Datalog popular among use cases with constantly evolving inputs such as static analysis in continuous integration and deployment pipelines. As a result, new logic programming…
Transpilation, or code translation, aims to convert source code from one programming language (PL) to another. It is beneficial for many downstream applications, from modernizing large legacy codebases to augmenting data for low-resource…