2 citations · 4 across the 4 of their papers we have counts for
4 papers
Contextual Moral Value Alignment Through Context-Based Aggregation
Pierre Dognin, Jesus Rios, Ronny Luss +7
Developing value-aligned AI agents is a complex undertaking and an ongoing challenge in the field of AI. Specifically within the domain of Large Language Models (LLMs), the capabil…
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf +16
The alignment of large language models is usually done by model providers to add or control behaviors that are common or universally understood across use cases and contexts. In co…
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models
Manish Nagireddy, Lamogha Chiazor, Moninder Singh +1
Current datasets for unwanted social bias auditing are limited to studying protected demographic features such as race and gender. In this work, we introduce a comprehensive benchm…
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman +3
Ensuring trustworthiness in machine learning (ML) models is a multi-dimensional task. In addition to the traditional notion of predictive performance, other notions such as privacy…