Cobus Greyling (6)

Disambiguation: Dynamic Context For Effective RAG Question Suggestions

Cobus Greyling

This approach reminds of a technique initially implemented by IBM Watson called disambiguation. Where ambiguous input...

FIT-RAG

Cobus Greyling

FIT-RAG: Are RAG Architectures Settling On A Standardised Approach?

As RAG is being used, vulnerabilities are emerging...

Challenges In Adopting Retrieval-Augmented Generation Solutions

Cobus Greyling

I have thoroughly examined some of the recent academic papers on RAG (Retrieval-Augmented Generation) and have...

Adaptive-RAG

Cobus Greyling

It is evident that there needs to be a balance between query time, quality in terms of performance, but also efficiency.

Large Language Models Excel At In-Context Learning (ICL)

Cobus Greyling

Studies have shown that, when supplied with a contextual reference at Inference, LLMs opt to make use of the contextual...

Retrieval Augmented Fine-Tuning (RAFT)

Cobus Greyling

Adapting Language Model to Domain Specific RAG...

Using RAFT, when presented with a question and a batch of retrieved...

DRAGIN: Dynamic RAG Based On Real-Time Information Needs Of LLMs

Cobus Greyling

A study introduced a novel approach to RAG but more importantly the study highlighted a number of shortcomings of...

A Study Comparing RAG & Fine-Tuning For Knowledge Base Use-Cases

Cobus Greyling

The selection of technology should be driven primarily by the requirements and goals of a particular use-case or...

RAT — Retrieval Augmented Thoughts

Cobus Greyling

Let me first start with a few general observations…

There is a tension between achieving efficiency within...

A Short History Of RAG

Cobus Greyling

One of the most popular themes currently around Large Language Models is the idea of Retrieval Augmented Generation...

Kore.ai Technical Blog

Disambiguation: Dynamic Context For Effective RAG Question Suggestions

This approach reminds of a technique initially implemented by IBM Watson called disambiguation. Where ambiguous input...

FIT-RAG

FIT-RAG: Are RAG Architectures Settling On A Standardised Approach?

Challenges In Adopting Retrieval-Augmented Generation Solutions

I have thoroughly examined some of the recent academic papers on RAG (Retrieval-Augmented Generation) and have...

Adaptive-RAG

It is evident that there needs to be a balance between query time, quality in terms of performance, but also efficiency.

Large Language Models Excel At In-Context Learning (ICL)

Studies have shown that, when supplied with a contextual reference at Inference, LLMs opt to make use of the contextual...

Retrieval Augmented Fine-Tuning (RAFT)

DRAGIN: Dynamic RAG Based On Real-Time Information Needs Of LLMs

A study introduced a novel approach to RAG but more importantly the study highlighted a number of shortcomings of...

A Study Comparing RAG & Fine-Tuning For Knowledge Base Use-Cases

RAT — Retrieval Augmented Thoughts

A Short History Of RAG

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