6 papers
Implementing Effective Changes in Software Projects to Optimize Runtimes and Minimize Defects
Kartik Gupta
The continuous evolution of software projects necessitates the implementation of changes to enhance performance and reduce defects. This research explores effective strategies for…
Iterative Auto-Annotation for Scientific Named Entity Recognition Using BERT-Based Models
Kartik Gupta
This paper presents an iterative approach to performing Scientific Named Entity Recognition (SciNER) using BERT-based models. We leverage transfer learning to fine-tune pretrained…
Measuring the Impact of Technical Debt on Development Effort in Software Projects
Kartik Gupta
Technical debt refers to the trade-offs between code quality and faster delivery, impacting future development with increased complexity, bugs, and costs. This study empirically an…
Fine-Tuning Qwen 2.5 3B for Realistic Movie Dialogue Generation
Kartik Gupta
The Qwen 2.5 3B base model was fine-tuned to generate contextually rich and engaging movie dialogue, leveraging the Cornell Movie-Dialog Corpus, a curated dataset of movie conversa…
Learning-Based Image Compression for Machines
Kartik Gupta, Kimberley Faria, Vikas Mehta
While learning based compression techniques for images have outperformed traditional methods, they have not been widely adopted in machine learning pipelines. This is largely due t…
Transfer Learning with Point Transformers
Kartik Gupta, Rahul Vippala, Sahima Srivastava
Point Transformers are near state-of-the-art models for classification, segmentation, and detection tasks on Point Cloud data. They utilize a self attention based mechanism to mode…