7 citations · 19 across the 6 of their papers we have counts for
6 papers
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting
Sanchit Ahuja, Kumar Tanmay, Hardik Hansrajbhai Chauhan +9
Despite the remarkable success of large language models (LLMs) in English, a significant performance gap remains in non-English languages. To address this, we introduce a novel app…
Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language we Prompt them in
Utkarsh Agarwal, Kumar Tanmay, Aditi Khandelwal +1
Ethical reasoning is a crucial skill for Large Language Models (LLMs). However, moral values are not universal, but rather influenced by language and culture. This paper explores h…
Do Moral Judgment and Reasoning Capability of LLMs Change with Language? A Study using the Multilingual Defining Issues Test
Aditi Khandelwal, Utkarsh Agarwal, Kumar Tanmay +1
This paper explores the moral judgment and moral reasoning abilities exhibited by Large Language Models (LLMs) across languages through the Defining Issues Test. It is a well known…
Ethical Reasoning over Moral Alignment: A Case and Framework for In-Context Ethical Policies in LLMs
Abhinav Rao, Aditi Khandelwal, Kumar Tanmay +2
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 t…
Probing the Moral Development of Large Language Models through Defining Issues Test
Kumar Tanmay, Aditi Khandelwal, Utkarsh Agarwal +1
In this study, we measure the moral reasoning ability of LLMs using the Defining Issues Test - a psychometric instrument developed for measuring the moral development stage of a pe…
DUBLIN -- Document Understanding By Language-Image Network
Kriti Aggarwal, Aditi Khandelwal, Kumar Tanmay +7
Visual document understanding is a complex task that involves analyzing both the text and the visual elements in document images. Existing models often rely on manual feature engin…