5 papers
An Efficient and Modular Framework for Targeted Harm Mitigation in LLMS
Roberto Campbell, Momin Abbas, Momin Abbass +6
Large Language Models (LLMs) are powerful zero-shot learners but remain prone to misalignment with human preferences, often producing biased, toxic, or otherwise harmful outputs. E…
A methodological analysis of prompt perturbations and their effect on attack success rates
Tiago Machado, Maysa Malfiza Garcia de Macedo, Rogerio Abreu de Paula +5
This work aims to investigate how different Large Language Models (LLMs) alignment methods affect the models' responses to prompt attacks. We selected open source models based on t…
A Comprehensive Evaluation framework of Alignment Techniques for LLMs
Muneeza Azmat, Momin Abbas, Maysa Malfiza Garcia de Macedo +9
As Large Language Models (LLMs) become increasingly integrated into real-world applications, ensuring their outputs align with human values and safety standards has become critical…
DECASTE: Unveiling Caste Stereotypes in Large Language Models through Multi-Dimensional Bias Analysis
Prashanth Vijayaraghavan, Soroush Vosoughi, Lamogha Chiazor +4
Recent advancements in large language models (LLMs) have revolutionized natural language processing (NLP) and expanded their applications across diverse domains. However, despite t…
Making Sense of Knowledge Intensive Processes: an Oil & Gas Industry Scenario
Juliana Jansen Ferreira, Vinícius Segura, Ana Fucs +1
Sensemaking is a constant and ongoing process by which people associate meaning to experiences. It can be an individual process, known as abduction, or a group process by which peo…