Enhancing Open-Domain Conversational Question Answering with Knowledge-Enhanced Models and Knowledge Graphs How knowledge-enhanced language models and knowledge graphs are advancing open-domain conversational question answering Author: Wenyi Pi (ORCID: 0009-0002-2884-2771 ) When searching for information on the website, it is common to come across a flood of
Latest findings for the use of Knowledge Graphs in the field of QA in multiple research directions
Unveiling Strategies to Enhance LLMs through Knowledge Graphs
Efficient creation of a stoplight report with data dashboard images Author: Yunzhong Zhang (ORCID: 0009–0002–8177–419X) Comparing data dashboards is crucial for understanding trends and performance differences. Traditionally, this task required manual effort, which was slow and sometimes inaccurate. Now, thanks to OpenAI’s GPT-4 with Vision (GPT-4V), we are able to automate and improve this process.
Unlocking the Power of Questions — A deep dive into Question Answering Systems
An Introduction to Retrieval Augmented Generation (RAG) and Knowledge Graph Author Qingqin Fang (ORCID: 0009–0003–5348–4264) Introduction Large Language Models (LLMs) have transformed the landscape of natural language processing, demonstrating exceptional proficiency in generating text that closely resembles human language.
Improving the performance of Large Language Models Author Dhruv Gupta (ORCID: 0009-0004-7109-5403) ChatGPT, which first came out in late 2022, took the world by storm. Since then, various LLM models and LLM based products such as Meta’s Llama and Google’s Gemini have emerged, demonstrating the power of LLMs.
How to efficiently retrieve information for different applications Author Wenyi Pi (ORCID: 0009-0002-2884-2771) This article aims to explore various ways in which Retrieval-Augmented Generation (RAG) can be utilised to retrieve information and generate responses effectively within the dialogue system. The rationale behind utilising RAG as well as potential ways in which it can be employed effectively will be covered.
An Introduction to RA-CM3, MuRAG, and RACE
Improving the performance and application of Large Language Models
Leveraging External Knowledge to Enhance the Descriptive Capabilities of AI Systems