2UrbanGirls on MSN

10 data collection techniques for NLP & LLM training

NLP and LLM teams often grow their training corpuses to improve model performance but they still do not always obtain ...
Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Ars Technica

Researchers show that training on “junk data” can lead to LLM “brain rot”

On the surface, it seems obvious that training an LLM with “high quality” data will lead to better performance than feeding it any old “low quality” junk you can find. Now, a group of researchers is ...
InfoWorld

Databricks’ TAO method to allow LLM training with unlabeled data

Test-time Adaptive Optimization can be used to increase the efficiency of inexpensive models, such as Llama, the company said. Data lakehouse provider Databricks has unveiled a new large language ...
Semiconductor Engineering

Silent Data Corruption: A Major Reliability Challenge in Large-Scale LLM Training (TU Berlin)

A new technical paper, “Exploring Silent Data Corruption as a Reliability Challenge in LLM Training,” was published by researchers at Technische Universitat Berlin. “As Large Language Models (LLMs) ...
Quanta Magazine

How ‘Embeddings’ Encode What Words Mean — Sort Of

A picture may be worth a thousand words, but how many numbers is a word worth? The question may sound silly, but it happens to be the foundation that underlies large language models, or LLMs — and ...