14 citations · 39 across the 29 of their papers we have counts for
5 papers · 1 filter
Cracking the Code: Evaluating Zero-Shot Prompting Methods for Providing Programming Feedback
Niklas Ippisch, Anna-Carolina Haensch, Jan Simson +3
Despite the growing use of large language models (LLMs) for providing feedback, limited research has explored how to achieve high-quality feedback. This case study introduces an ev…
Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study
Bolei Ma, Berk Yoztyurk, Anna-Carolina Haensch +5
In recent research, large language models (LLMs) have been increasingly used to investigate public opinions. This study investigates the algorithmic fidelity of LLMs, i.e., the abi…
United in Diversity? Contextual Biases in LLM-Based Predictions of the 2024 European Parliament Elections
Leah von der Heyde, Anna-Carolina Haensch, Alexander Wenz +1
"Synthetic samples" based on large language models (LLMs) have been argued to serve as efficient alternatives to surveys of humans, assuming that their training data includes infor…
Vox Populi, Vox AI? Using Language Models to Estimate German Public Opinion
Leah von der Heyde, Anna-Carolina Haensch, Alexander Wenz
The recent development of large language models (LLMs) has spurred discussions about whether LLM-generated "synthetic samples" could complement or replace traditional surveys, cons…
The Potential and Challenges of Evaluating Attitudes, Opinions, and Values in Large Language Models
Bolei Ma, Xinpeng Wang, Tiancheng Hu +4
Recent advances in Large Language Models (LLMs) have sparked wide interest in validating and comprehending the human-like cognitive-behavioral traits LLMs may capture and convey. T…