7 papers · 1 filter
Exploring Human Perceptions of AI Responses: Insights from a Mixed-Methods Study on Risk Mitigation in Generative Models
Heloisa Candello, Muneeza Azmat, Uma Sushmitha Gunturi +7
With the rapid uptake of generative AI, investigating human perceptions of generated responses has become crucial. A major challenge is their `aptitude' for hallucinating and gener…
Out-of-Distribution Detection using Synthetic Data Generation
Momin Abbas, Muneeza Azmat, Raya Horesh +1
Distinguishing in- and out-of-distribution (OOD) inputs is crucial for reliable deployment of classification systems. However, OOD data is typically unavailable or difficult to col…
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…
SPRI: Aligning Large Language Models with Context-Situated Principles
Hongli Zhan, Muneeza Azmat, Raya Horesh +2
Aligning Large Language Models to integrate and reflect human values, especially for tasks that demand intricate human oversight, is arduous since it is resource-intensive and time…
CharED: Character-wise Ensemble Decoding for Large Language Models
Kevin Gu, Eva Tuecke, Dmitriy Katz +3
Large language models (LLMs) have shown remarkable potential for problem solving, with open source models achieving increasingly impressive performance on benchmarks measuring area…