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 ...
InfoQ

MIT's Recursive Language Models Improve Performance on Long-Context Tasks

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance ...
GitHub

Modern JavaScript runtime in Python

Note: jsrun is under development. Expect breaking changes between minor versions. One of the most compelling use cases for jsrun is building safe execution environments for AI agents. When LLMs ...
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 ...
GitHub

Block or report zhangyu345293721

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning … ...