12 citations · 14 across the 6 of their papers we have counts for
7 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
Muse Spark Safety & Preparedness Report
Cristina Menghini, Peter Ney, Hamza Kwisaba +117
Muse Spark is the latest large language model developed by Meta. In this report, we first present evaluations for catastrophic risk domains under Meta's Advanced AI Scaling Framewo…
"Hello, is this Anna?": Unpacking the Lifecycle of Pig-Butchering Scams
Rajvardhan Oak, Zubair Shafiq
Pig-butchering scams have emerged as a complex form of fraud that combines elements of romance, investment fraud, and advanced social engineering tactics to systematically exploit…
Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms
Rajvardhan Oak, Muhammad Haroon, Claire Jo +2
Social media platforms utilize Machine Learning (ML) and Artificial Intelligence (AI) powered recommendation algorithms to maximize user engagement, which can result in inadvertent…
Towards Safer Social Media Platforms: Scalable and Performant Few-Shot Harmful Content Moderation Using Large Language Models
Akash Bonagiri, Lucen Li, Rajvardhan Oak +3
The prevalence of harmful content on social media platforms poses significant risks to users and society, necessitating more effective and scalable content moderation strategies. C…
Understanding Underground Incentivized Review Services
Rajvardhan Oak, Zubair Shafiq
While human factors in fraud have been studied by the HCI and security communities, most research has been directed to understanding either the victims' perspectives or prevention…
Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks
Vikash Sehwag, Rajvardhan Oak, Mung Chiang +1
With increasing expressive power, deep neural networks have significantly improved the state-of-the-art on image classification datasets, such as ImageNet. In this paper, we invest…