5 citations · 6 across the 3 of their papers we have counts for
3 papers
Process Matters more than Output for Distinguishing Humans from Machines
Milena Rmus, Mathew D. Hardy, Thomas L. Griffiths +1
Reliable human-machine discrimination is becoming increasingly important as large language models and autonomous agents are deployed in online settings. Existing approaches evaluat…
When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1
R. Thomas McCoy, Shunyu Yao, Dan Friedman +2
In "Embers of Autoregression" (McCoy et al., 2023), we showed that several large language models (LLMs) have some important limitations that are attributable to their origins in ne…
Bias amplification in experimental social networks is reduced by resampling
Mathew D. Hardy, Bill D. Thompson, P. M. Krafft +1
Large-scale social networks are thought to contribute to polarization by amplifying people's biases. However, the complexity of these technologies makes it difficult to identify th…