Refining Large Language Models for Tabular Data Analysis in Business Domain by Laymen Text-Reference-Cited by-同舟云学术

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Refining Large Language Models for Tabular Data Analysis in Business Domain by Laymen Text

Published:2024-04-04 Issue: Volume:14 Page:1-5
ISSN:
Container-title:2024 International Research Conference on Smart Computing and Systems Engineering (SCSE)
language:
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Author:

Nirusanan Thavachelvam¹,Prasanth Senthan²,Banujan Kuhaneswaran³,Kumara Samantha¹

Affiliation:

1. Sabaragamuwa University of Sri Lanka,Department of Computing and Information Systems,Belihuloya,Sri Lanka

2. Sabaragamuwa University of Sri Lanka,Department of Physical Sciences and Technology,Belihuloya,Sri Lanka

3. Independent Researcher,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10550188/10550445/10550809.pdf?arnumber=10550809

Reference20 articles.

1. Generative AI

2. Self-Instruct: Aligning Language Models with Self-Generated Instructions

3. It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners

4. GPT-NeoX-20B: An Open-Source Autoregressive Language Model

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