13 citations · 14 across the 5 of their papers we have counts for
7 papers
Exploring and Developing a Pre-Model Safeguard with Draft Models
Hongyu Cai, Arjun Arunasalam, Yiming Liang +2
Large Language Model (LLM) alignment remains vulnerable to jailbreak attacks that elicit unsafe responses, motivating pre-model and post-model guards. Pre-model guards audit the sa…
International Students and Scams: At Risk Abroad
Katherine Zhang, Arjun Arunasalam, Pubali Datta +1
International students (IntlS) in the US refer to foreign students who acquire student visas to study in the US, primarily in higher education. As IntlS arrive in the US, they face…
Investigating the Impact of Dark Patterns on LLM-Based Web Agents
Devin Ersoy, Brandon Lee, Ananth Shreekumar +4
As users increasingly turn to large language model (LLM) based web agents to automate online tasks, agents may encounter dark patterns: deceptive user interface designs that manipu…
Implicit Values Embedded in How Humans and LLMs Complete Subjective Everyday Tasks
Arjun Arunasalam, Madison Pickering, Z. Berkay Celik +1
Large language models (LLMs) can underpin AI assistants that help users with everyday tasks, such as by making recommendations or performing basic computation. Despite AI assistant…
Understanding Users' Security and Privacy Concerns and Attitudes Towards Conversational AI Platforms
Mutahar Ali, Arjun Arunasalam, Habiba Farrukh
The widespread adoption of conversational AI platforms has introduced new security and privacy risks. While these risks and their mitigation strategies have been extensively resear…
Rethinking How to Evaluate Language Model Jailbreak
Hongyu Cai, Arjun Arunasalam, Leo Y. Lin +2
Large language models (LLMs) have become increasingly integrated with various applications. To ensure that LLMs do not generate unsafe responses, they are aligned with safeguards t…
Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions
Yufan Chen, Arjun Arunasalam, Z. Berkay Celik
Users seek security & privacy (S&P) advice from online resources, including trusted websites and content-sharing platforms. These resources help users understand S&P technologies a…