A deep learning framework combining bird swarm optimization with adaptive image segmentation achieved 99.05 percent accuracy ...

A comprehensive Python tutorial outlines an end-to-end framework enabling engineers without programming expertise to ...

Low-rank adaptation fine-tunes a frozen model by learning small low-rank update matrices rather than changing every original parameter. This guide explains the mechanism, trade-offs, evaluation, and ...

Fine-tuning the TerraMind Earth Observation foundation model for water segmentation using Sentinel-1 SAR imagery. - Sina-Mohammadi/terramind-sentinel1-water-segmentation ...

Salesforce's SRD distills hindsight into foresight, rescuing agent RL when rewards vanish and lifting success from 0% to 60.6 ...

This study provides a valuable mapping of how genomic variation from a large collection of Klebsiella pneumoniae clinical isolates shapes bacterial fitness across 214 conditions. Solid data describe ...

This project develops and evaluates machine learning models to predict passenger survival aboard the RMS Titanic using the Kaggle Titanic: Machine Learning from Disaster dataset. The project follows ...

Instruction tuning uses examples of instructions and desired responses to make a pretrained model more useful, controllable, ...

Neural networks are called "black boxes." This means that while you get an answer when you input data, you cannot see what is happening inside.However, you can peek inside smaller networks. What is a ...

Veovesna SLM is an experimental Indonesian-language small language model built from scratch using a custom decoder-only Transformer architecture in PyTorch. The released checkpoint is Run B-Control, ...

A benchmark for temporal reasoning over patient timelines: given a question about when something happened in one patient's record, retrieve the passages that support the correct answer rather than ...