no code implementations • 18 Apr 2024 • Abhinav Rao, Akhila Yerukola, Vishwa Shah, Katharina Reinecke, Maarten Sap
We introduce NormAd, a novel dataset, which includes 2. 6k stories that represent social and cultural norms from 75 countries, to assess the ability of LLMs to adapt to different granular levels of socio-cultural contexts such as the country of origin, its associated cultural values, and prevalent social norms.
no code implementations • 11 Oct 2023 • Abhinav Rao, Aditi Khandelwal, Kumar Tanmay, Utkarsh Agarwal, Monojit Choudhury
In this position paper, we argue that instead of morally aligning LLMs to specific set of ethical principles, we should infuse generic ethical reasoning capabilities into them so that they can handle value pluralism at a global scale.
1 code implementation • 24 May 2023 • Abhinav Rao, Sachin Vashistha, Atharva Naik, Somak Aditya, Monojit Choudhury
Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate output behavior, privacy and security breaches, offensive outputs, and violations of content regulator policies.
1 code implementation • 10 Dec 2022 • Abhinav Rao, Ho Thi-Nga, Chng Eng-Siong
The focus languages are English, Mandarin, and Malay which are three of the most popular languages in Singapore.