Papers by Anna-Carolina Haensch
Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models (2026.acl-long)
Copied to clipboard
| Challenge: | Existing studies focus on generating closed-ended survey responses with large language models, whereas LLMs are typically trained to generate open-ended text. |
| Approach: | They evaluate the impact of various Survey Response Generation Methods on simulated responses by generating closed-ended responses from large language models. |
| Outcome: | The proposed methods perform best in individual-level and subpopulation-level alignment. |
Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation (2026.eacl-long)
Copied to clipboard
Bolei Ma, Yong Cao, Indira Sen, Anna-Carolina Haensch, Frauke Kreuter, Barbara Plank, Daniel Hershcovich
| Challenge: | Large Language Models (LLMs) are increasingly used to simulate public opinion and other social phenomena. |
| Approach: | They argue that open-endedness is essential for realistic social simulations . they argue that it captures expressiveness and individuality . |
| Outcome: | The proposed frameworks can improve measurement and design, support exploration of unanticipated views, and reduce researcher-imposed directive bias. |
The Potential and Challenges of Evaluating Attitudes, Opinions, and Values in Large Language Models (2024.findings-emnlp)
Copied to clipboard
Bolei Ma, Xinpeng Wang, Tiancheng Hu, Anna-Carolina Haensch, Michael Hedderich, Barbara Plank, Frauke Kreuter
| Challenge: | Recent advances in Large Language Models have sparked interest in validating human-like cognitive-behavioral traits. |
| Approach: | They examine whether LLM outputs reflect human-like cognitive-behavioral traits . they find that measuring AOVs embedded within LLMs remains opaque . |
| Outcome: | The proposed model can be used to evaluate human-like cognitive-behavioral traits . the proposed model could be used in writing assistants and other applications . |
Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study (2025.acl-long)
Copied to clipboard
Bolei Ma, Berk Yoztyurk, Anna-Carolina Haensch, Xinpeng Wang, Markus Herklotz, Frauke Kreuter, Barbara Plank, Matthias Aßenmacher
| Challenge: | Recent advances in large language models have generated significant interest in their potential for synthetic data generation across various domains. |
| Approach: | They use open-ended survey data from the German Longitudinal Election Studies to prompt different LLMs to generate synthetic public opinions reflective of German subpopulations by incorporating demographic features into the persona prompts. |
| Outcome: | The LLM performs better for supporters of left-leaning parties like The Greens and The Left compared to other parties, and matches the least with the right-party AfD. |
Can Large Language Models Advance Crosswalks? The Case of Danish Occupation Codes (2025.naacl-srw)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are used to map classification systems to each other . however, their use is labor-intensive and requires domain expertise . |
| Approach: | They propose a prompt-based framework where LLMs perform similarity assessments between classification codes and identify final mappings through a guided decision process. |
| Outcome: | The proposed framework shows that LLMs perform better than the embedding-based framework in creating crosswalks. |
Capabilities and Evaluation Biases of Large Language Models in Classical Chinese Poetry Generation: A Case Study on Tang Poetry (2026.findings-acl)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are increasingly applied to creative domains, yet performance in classical Chinese poetry generation and evaluation remains poorly understood. |
| Approach: | They propose a framework that combines computational metrics, LLM-as-a-judge assessment, and human expert validation to evaluate large language models. |
| Outcome: | The proposed framework evaluates state-of-the-art LLMs across multiple dimensions of poetic quality in Tang poetry generation. |