| Title: |
Evaluating the Efficacy of Prompting Techniques for Debiasing Language Model Outputs (Student Abstract) |
| Authors: |
Furniturewala, Shaz; Jandial, Surgan; Java, Abhinav; Shahid, Simra; Banerjee, Pragyan; Krishnamurthy, Balaji; Bhatia, Sumit; Jaidka, Kokil |
| Source: |
Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 21: IAAI-24, EAAI-24, AAAI-24 Student Abstracts, Undergraduate Consortium and Demonstrations; 23492-23493 ; 2374-3468 ; 2159-5399 |
| Publisher Information: |
Association for the Advancement of Artificial Intelligence |
| Publication Year: |
2024 |
| Collection: |
Association for the Advancement of Artificial Intelligence: AAAI Publications |
| Subject Terms: |
LLM; Debiasing; Fairness; Zeroshot; Text Generation |
| Description: |
Achieving fairness in Large Language Models (LLMs) continues to pose a persistent challenge, as these models are prone to inheriting biases from their training data, which can subsequently impact their performance in various applications. There is a need to systematically explore whether structured prompting techniques can offer opportunities for debiased text generation by LLMs. In this work, we designed an evaluative framework to test the efficacy of different prompting techniques for debiasing text along different dimensions. We aim to devise a general structured prompting approach to achieve fairness that generalizes well to different texts and LLMs. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISBN: |
978-2-349-22349-4; 2-349-22349-3 |
| Relation: |
https://ojs.aaai.org/index.php/AAAI/article/view/30443/32533; https://ojs.aaai.org/index.php/AAAI/article/view/30443/32534; https://ojs.aaai.org/index.php/AAAI/article/view/30443 |
| DOI: |
10.1609/aaai.v38i21.30443 |
| Availability: |
https://ojs.aaai.org/index.php/AAAI/article/view/30443; https://doi.org/10.1609/aaai.v38i21.30443 |
| Rights: |
Copyright (c) 2024 Association for the Advancement of Artificial Intelligence |
| Accession Number: |
edsbas.83351977 |
| Database: |
BASE |