3 papers
cs.AI2026
Do Large Language Models Know What They Don't Know II? A Fully Behavioral, Non-Cognitive Measure of Epistemic Honesty
Ali Şenol, H. Russell Bernard, Huan Liu
Large Language Models (LLMs) are frequently confident, eloquent, and well versed. A natural question arises: do they know what they don't know? To answer this question, we borrow t…
cs.SI2025
Fediverse Sharing: Cross-Platform Interaction Dynamics between Threads and Mastodon Users
Ujun Jeong, Alimohammad Beigi, Anique Tahir +3
Traditional social media platforms, once envisioned as digital town squares, now face growing criticism over corporate control, content moderation, and privacy concerns. Events suc…
cs.CL2024
Assessing the Impact of Conspiracy Theories Using Large Language Models
Bohan Jiang, Dawei Li, Zhen Tan +5
Measuring the relative impact of CTs is important for prioritizing responses and allocating resources effectively, especially during crises. However, assessing the actual impact of…