IEEE

AID-SQL: Adaptive In-Context Learning of Text-to-SQL with Difficulty-Aware Instruction and Retrieval-Augmented Generation

Abstract: Recent research in Text-to-SQL translation has primarily adopted in-context learning methods leveraging large language models (LLMs), achieving significant progress. However, these methods ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Geeky Gadgets

Is the AI Bubble Real, or Is Relentless Learning Quietly Winning Today?

What if the so-called “AI bubble” isn’t a bubble at all? Imagine a world where artificial intelligence doesn’t just plateau or implode under the weight of its own hype but instead grows smarter, more ...
blockchain

Continual Learning with Nested Optimization: Breakthrough in Long Context AI Processing by Google Research

According to Jeff Dean, a new AI approach from Google Research utilizes nested optimization techniques to significantly advance continual learning, particularly for ...
Scientific Research Publishing

Cubillas, J.J., Ramos, M.I., Jurado, J.M. and Feito, F.R. (2022) A Machine Learning Model for Early Prediction of Crop Yield, Nested in a Web Application in the Cloud: A Case ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...
GitHub

nested-queries

Add a description, image, and links to the nested-queries topic page so that developers can more easily learn about it.
marktechpost

LLMs Can Learn Complex Math from Just One Example: Researchers from University of Washington, Microsoft, and USC Unlock the Power of 1-Shot Reinforcement Learning with ...

Recent advancements in LLMs such as OpenAI-o1, DeepSeek-R1, and Kimi-1.5 have significantly improved their performance on complex mathematical reasoning tasks. Reinforcement Learning with Verifiable ...
IEEE

MGRR-SQL: Multi-Granularity Relevant Retrieval-Based in-Context Learning Approach for Text-to-SQL Generation

Abstract: In-Context learning serves as a vital component for enhancing Text-to-SQL task performance. However, current in-context learning methodologies for Text-to-SQL applications fail to ...