2 citations · 9 across the 11 of their papers we have counts for
11 papers
Representational Similarity and Model Behavior in Multi-Agent Interaction
Yujin Potter, Seun Eisape, Shiyang Lai +6
Researchers have shown that neural similarity among humans predicts social closeness and cooperative success, whereas innovation often emerges from interactions among dissimilar in…
Peer-Preservation in Frontier Models
Yujin Potter, Nicholas Crispino, Vincent Siu +2
Recent work has found that frontier AI models can exhibit misaligned behaviors in pursuit of assigned goals. We demonstrate that models can also exhibit misaligned behaviors in def…
VMDT: Decoding the Trustworthiness of Video Foundation Models
Yujin Potter, Zhun Wang, Nicholas Crispino +11
As foundation models become more sophisticated, ensuring their trustworthiness becomes increasingly critical; yet, unlike text and image, the video modality still lacks comprehensi…
Biased AI improves human performance but reduces perceived helpfulness
Shiyang Lai, Jiwoong Choi, Junsol Kim +3
Artificial intelligence (AI) increasingly shapes how people think, engage, and evaluate information. To minimize risk, most current systems are designed to present as ideologically…
Frontier AI's Impact on the Cybersecurity Landscape
Yujin Potter, Wenbo Guo, Zhun Wang +6
The impact of frontier AI (i.e., AI agents and foundation models) in cybersecurity is rapidly increasing. In this paper, we comprehensively analyze this trend through multiple aspe…
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen +22
Multimodal foundation models (MMFMs) play a crucial role in various applications, including autonomous driving, healthcare, and virtual assistants. However, several studies have re…
Political Neutrality in AI Is Impossible- But Here Is How to Approximate It
Jillian Fisher, Ruth E. Appel, Chan Young Park +9
AI systems often exhibit political bias, influencing users' opinions and decisions. While political neutrality-defined as the absence of bias-is often seen as an ideal solution for…
Hidden Persuaders: LLMs' Political Leaning and Their Influence on Voters
Yujin Potter, Shiyang Lai, Junsol Kim +2
How could LLMs influence our democracy? We investigate LLMs' political leanings and the potential influence of LLMs on voters by conducting multiple experiments in a U.S. president…
Future of Algorithmic Organization: Large-Scale Analysis of Decentralized Autonomous Organizations (DAOs)
Tanusree Sharma, Yujin Potter, Kornrapat Pongmala +4
Decentralized Autonomous Organizations (DAOs) resemble early online communities, particularly those centered around open-source projects, and present a potential empirical framewor…
Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis
Tanusree Sharma, Yujin Potter, Zachary Kilhoffer +3
How AI models should deal with political topics has been discussed, but it remains challenging and requires better governance. This paper examines the governance of large language…
Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation
Shiyang Lai, Yujin Potter, Junsol Kim +3
Large language model behavior is shaped by the language of those with whom they interact. This capacity and their increasing prevalence online portend that they will intentionally…