most citedLLM hallucinations in the wild: Large-scale evidence from non-existent citations

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DL2026

A robust association between LLM use and scientific productivity: Assessing stopping-time selection

Keigo Kusumegi, Xinyu Yang, Paul Ginsparg +3

Renault, Bergeaud, and Bosquet (hereafter RBB) argue that dating LLM adoption as the first month in which an author's abstract is flagged induces a stopping-time selection that can…

cs.LG2026

Benchmark Datasets for Lead-Lag Forecasting on Social Platforms

Kimia Kazemian, Zhenzhen Liu, Yangfanyu Yang +9

Social and collaborative platforms emit multivariate time-series traces in which early interactions -- such as views, likes, or downloads -- are followed, sometimes months or years…

physics.soc-ph2026

Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment

Binglu Wang, Weixin Liang, Jiahui Xue +4

Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally distributed. Here we test whe…

cs.DL20261 cited

LLM hallucinations in the wild: Large-scale evidence from non-existent citations

Zhenyue Zhao, Yihe Wang, Toby Stuart +3

Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and consequences of this hallucinat…

cs.SI2025

Survivors, Complainers, and Borderliners: Upward Bias in Online Discussions of Academic Conference Reviews

Hangxiao Zhu, Yian Yin, Yu Zhang

Online discussion platforms, such as community Q&A sites and forums, have become important hubs where academic conference authors share and seek information about the peer review p…