Cobus Greyling (2)

Craft Successful Conversational User Interfaces: Align User Intent With Developed Intent

In this article I illustrate how to achieve intent alignment by making use of the Kore.ai XO Platform Intent Discovery...

A Benchmark for Verifying Chain-Of-Thought

A Chain-of-Thought is only as strong as its weakest link; a recent study from Google Research created a benchmark for...

Seven RAG Engineering Failure Points

Retrieval-Augmented Generation (RAG) systems remains a compelling solution to the challenge of relevant up-to-date...

UniMS-RAG: Unified Multi-Source RAG for Personalised Dialogue

This study explores how the RAG process can be decomposed, adding elements like multi-document retrieval, memory and...

Chain-of-Symbol Prompting (CoS) For Large Language Models

LLMs need to understand a virtual spatial environment described through natural language while planning & achieving...

Concise Chain-of-Thought (CCoT) Prompting

Traditional CoT comes at a cost of increased output token usage, CCoT prompting is a prompt-engineering technique which...

Understanding LLM User Experience & Expectation

This study surfaces valuable insights into the frequency of LLM use together with user intents, expectations and...

Meta Taxonomy Of LLM Correction & Refinement

A number of LLM techniques and classes of implementation are emerging, a fairly recent study created a meta taxonomy of...

Considering Large Language Model Reasoning Step Length

When using Chain of Thought, what is the optimal number of steps to use?

Chain Of Natural Language Inference (CoNLI)

Hallucination is categorised into subcategories of Context-Free Hallucination, Ungrounded Hallucination &...