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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.
VentureBeat

DeepMind’s GenRM improves LLM accuracy by having models verify their own outputs

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Large language models (LLMs) are prone to ...
ascopubs.org

Ensuring Reliability of Curated Electronic Health Record–Derived Data: The Validation of Accuracy for Large Language Model–/Machine Learning–Extracted Information and ...

Early-Stage Breast Cancer in Women Younger Than 50 Years: Comparing American Joint Committee on Cancer Anatomic and Prognostic Stages With Partitioning Around Medoids Clusters in SEER Data Large ...
InfoQ

The Data Backbone of LLM Systems

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
InfoWorld

How to test large language models

Companies investing in generative AI find that testing and quality assurance are two of the most critical areas for improvement. Here are four strategies for testing LLMs embedded in generative AI ...
Forbes

What Happens When LLM’s Run Out Of Useful Data?

Most of us feel like we’re drowning in data. And yet, in the world of generative AI, a looming data shortage is keeping some researchers up at night. GenAI is unquestionably a technology whose ...
eWeek

9 Best Large Language Models For Your Tech Stack

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...