8 citations · 20 across the 21 of their papers we have counts for
4 papers · 1 filter
Data Value in the Age of Scaling: Understanding LLM Scaling Dynamics Under Real-Synthetic Data Mixtures
Haohui Wang, Jingyuan Qi, Jianpeng Chen +9
The rapid progress of large language models (LLMs) is fueled by the growing reliance on datasets that blend real and synthetic data. While synthetic data offers scalability and cos…
AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models
Chinnappa Guggilla, Budhaditya Roy, Trupti Ramdas Chavan +2
Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. T…
Evaluating Query Efficiency and Accuracy of Transfer Learning-based Model Extraction Attack in Federated Learning
Sayyed Farid Ahamed, Sandip Roy, Soumya Banerjee +6
Federated Learning (FL) is a collaborative learning framework designed to protect client data, yet it remains highly vulnerable to Intellectual Property (IP) threats. Model extract…
RADEP: A Resilient Adaptive Defense Framework Against Model Extraction Attacks
Amit Chakraborty, Sayyed Farid Ahamed, Sandip Roy +6
Machine Learning as a Service (MLaaS) enables users to leverage powerful machine learning models through cloud-based APIs, offering scalability and ease of deployment. However, the…