4 citations · 7 across the 6 of their papers we have counts for
6 papers
Semantic Structure of Feature Space in Large Language Models
Austin C. Kozlowski, Andrei Boutyline
We show that the geometric relations between semantic features in large language models' hidden states closely mirror human psychological associations. We construct feature vectors…
PreScience: A Dataset and Benchmark for Scientific Forecasting
Anirudh Ajith, Amanpreet Singh, Jay DeYoung +7
Can AI systems trained on the existing scientific record forecast the advances that will follow? We introduce PreScience, a dataset and benchmark for scientific forecasting built a…
The (Short-Term) Effects of Large Language Models on Unemployment and Earnings
Danqing Chen, Carina Kane, Austin Kozlowski +2
Large Language Models have spread rapidly since the release of ChatGPT in late 2022, accompanied by claims of major productivity gains but also concerns about job displacement. Thi…
Semantic Structure in Large Language Model Embeddings
Austin C. Kozlowski, Callin Dai, Andrei Boutyline
Psychological research consistently finds that human ratings of words across diverse semantic scales can be reduced to a low-dimensional form with relatively little information los…
LLM Social Simulations Are a Promising Research Method
Jacy Reese Anthis, Ryan Liu, Sean M. Richardson +5
Accurate and verifiable large language model (LLM) simulations of human research subjects promise an accessible data source for understanding human behavior and training new AI sys…
In Silico Sociology: Forecasting COVID-19 Polarization with Large Language Models
Austin C. Kozlowski, Hyunku Kwon, James A. Evans
By training deep neural networks on massive archives of digitized text, large language models (LLMs) learn the complex linguistic patterns that constitute historic and contemporary…