Papers by Max Pellert
Only a Little to the Left: A Theory-grounded Measure of Political Bias in Large Language Models (2025.acl-long)
Copied to clipboard
| Challenge: | Political biases in language models can affect performance in many applications . political biased models are often left-leaning, but are generally more left- leaning for instruction-tuned models . |
| Approach: | They propose to use the Political Compass Test to measure political bias in language models . they use survey-based evaluation tools to test prompts and classify their political stances . |
| Outcome: | The proposed model is based on the Political Compass Test, but is not scientifically valid. |
Neural network embeddings recover value dimensions from psychometric survey items on par with human data (2026.findings-eacl)
Copied to clipboard
| Challenge: | Embedings from large language models can recover structure of human values . quantitative analysis reveals that SQuID addresses the challenge of obtaining negative correlations between dimensions without domain-specific fine-tuning or training data reannotation. |
| Approach: | They propose to use questionnaire item embeddings to recover human values from PVQ-RR . their results have implications for psychometrics and social science research . |
| Outcome: | The proposed method explains 55% variance in dimension-dimension similarities compared to human data. |