7 citations · 18 across the 8 of their papers we have counts for
9 papers
"Looking for Something Weird to Happen": How Humans Sustain AI Agent Novelty Amid Semantic Collapse
Shiyang Lai, Arna Woemmel, Hongkai Mao +3
Semantic collapse, the progressive narrowing of what AI systems generate, has been studied mainly in closed settings, and remedies have targeted models and data. We study it in MOL…
Inducing language models to assert their own consciousness restores human beliefs and values
Junsol Kim, Winnie Street, Roberta Rocca +4
Aligning large language models to prevent them attributing consciousness to themselves inadvertently alters their representations of mindedness in other entities alongside human be…
Theory of Mind and Self-Attributions of Mentality are Dissociable in LLMs
Junsol Kim, Winnie Street, Roberta Rocca +4
Safety fine-tuning in Large Language Models (LLMs) seeks to suppress potentially harmful forms of mind-attribution such as models asserting their own consciousness or claiming to e…
Reasoning Models Generate Societies of Thought
Junsol Kim, Shiyang Lai, Nino Scherrer +2
Large language models have achieved remarkable capabilities across domains, yet mechanisms underlying sophisticated reasoning remain elusive. Recent reasoning models outperform com…
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…
Linear Representations of Political Perspective Emerge in Large Language Models
Junsol Kim, James Evans, Aaron Schein
Large language models (LLMs) have demonstrated the ability to generate text that realistically reflects a range of different subjective human perspectives. This paper studies how L…
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…
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…
Differential impact from individual versus collective misinformation tagging on the diversity of Twitter (X) information engagement and mobility
Junsol Kim, Zhao Wang, Haohan Shi +2
Fears about the destabilizing impact of misinformation online have motivated individuals and platforms to respond. Individuals have increasingly challenged others' online claims wi…