4 papers
Measuring Behavior Portability in Large Language Models
Tianjia Dong, Nadav Kunievsky, James A. Evans
Large language models are increasingly deployed as autonomous decision makers, yet the behavioral mapping they exhibit can vary substantially across decision environments that are…
Measuring Intent Comprehension in LLMs
Nadav Kunievsky, James A. Evans
People judge interactions with large language models (LLMs) as successful when outputs match what they want, not what they type. Yet LLMs are trained to predict the next token sole…
Narrative Flattening: How Post-Training Compresses Thematic, Affective, and Stylistic Variation in LLM Fiction
Zehan Li, Yutong Zhu, Siyang Wu +2
Large language models produce fluent fiction, yet their creative output is widely seen as flat. We ask where this quality originates in the training and whether it affects differen…
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…