146 citations · 173 across the 10 of their papers we have counts for
4 papers · 1 filter
A Mechanistic View of Authority Hierarchy in LLM Sycophancy
Emil Joswin, Srujananjali Medicherla, Priyanka Mary Mammen
Authority bias poses a critical safety concern in language models: models systematically prioritize social cues from authority figures over factual consistency, swaying their answe…
Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models
Priyanka Mary Mammen, Emil Joswin, Shankar Venkitachalam
Prior research demonstrates that performance of language models on reasoning tasks can be influenced by suggestions, hints and endorsements. However, the influence of endorsement s…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
Detecting Natural Language Biases with Prompt-based Learning
Md Abdul Aowal, Maliha T Islam, Priyanka Mary Mammen +1
In this project, we want to explore the newly emerging field of prompt engineering and apply it to the downstream task of detecting LM biases. More concretely, we explore how to de…