Explaining LLMs for RAG and Summary | by Daniel Klitzke | November 2024
A fast, low-resource method using similarity-based attributionInformation flow between an input document and its summary calculated using the proposed explainability ...
Tag: LLMs
WEBRL: A Self-Evolving Online Curriculum Reinforcement Learning Framework for Training High-Performing Web Agents with Open LLMs
Large language models (LLMs) have demonstrated exceptional capabilities in understanding human language, reasoning, and knowledge acquisition, suggesting their potential to ...
How and why to use LLMs for fragment-based information retrieval | by Carlo Perón | October 2024
Recover pipeline — Image by the authorIn this article, my goal is to explain how and why it is beneficial ...
Nova: An iterative planning and search approach to improve the novelty and diversity of ideas generated by large language models (LLMs)
Innovation in science is essential to human progress because it drives advances in a wide range of industries, including technology, ...
This AI research from Cohere for AI compares fusion to data blending as a recipe for creating high-performing aligned LLMs
Large language models (LLMs) have revolutionized the field of artificial intelligence by performing a wide range of tasks in different ...
RealHumanEval: A web interface to measure the ability of LLMs to help programmers
The increasing reliance on large language models for coding support raises an important problem: what is the best way to ...
Nvidia AI introduces the Normalized Transformer (nGPT): a hypersphere-based transformer that achieves 4-20x faster training and improved stability for LLMs
The rise of Transformer-based models has significantly advanced the field of natural language processing. However, training these models is often ...
Leveraging smaller LLMs for enhanced recovery-augmented generation (RAG)
Call-3.2–1 B-Instruct and LanceDBAbstract: Retrieval Augmented Generation (RAG) combines large language models with external knowledge sources to produce more accurate ...
How Large Language Models (LLMs) Can Perform Multiple Computationally Distinct In-Context Learning (ICL) Tasks Simultaneously
Large language models (LLMs) have demonstrated remarkable mastery in in-context learning (ICL), which is a technique that teaches them to ...
Katanemo Open Source Arch-Function: A set of large language models (LLMs) that promise ultra-fast speeds in function calling tasks for agent workflows
One of the biggest obstacles organizations face is implementing large language models (LLMs) to handle complex workflows effectively. Speed, flexibility, ...
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