MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

Learning Hard Concepts Gets Easier When You Test Patterns and Reduce Jargon

Schema fit enables hard ideas to click, learn assimilation vs accommodation and use pattern testing to understand faster ...
EurekAlert!

Robust long-tailed learning under label noise

Real-world data typically exhibits long-tailed class distribution and contains label noise. Previous long-tail learning ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...
Frontiers

Multi-modal Learning with Large-scale Models

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...
Chromatography Online

AI/ML in Practice: Emery Boston explores assisted active learning (AAL)

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...