Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
IEEE

Generation of Optimized Solidity Code for Machine Learning Models using LLMs

Abstract: In this paper, we propose LMST - an approach for Large Language Model (LLM) based conversion of the PyTorch code of an ML model into Solidity. Beyond mere correctness, we try to achieve gas ...
IEEE

Digital In-Memory Compute for Machine Learning Applications With Input and Model Security

Abstract: Digital in-memory compute (IMC) architectures allow for a balance of the high accuracy and precision necessary for many machine learning applications, with high data reuse and parallelism to ...