arXiv AI
Multicalibration for Unbiased Model-Based Prevalence Estimation
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arXiv Machine Learning
Jun 2
How to Correctly Report LLM-as-a-Judge Evaluations
arXiv:2511. 21140v4 Announce Type: replace Abstract: Large language models (LLMs) are widely used as scalable evaluators of model responses in lieu of human annotators.
arXiv AI
Jul 21
"Not in My Backyard": LLMs Uncover Online and Offline Social Biases Against Homelessness
arXiv:2508. 13187v4 Announce Type: replace-cross Abstract: Homelessness is a persistent social challenge, impacting millions worldwide.
arXiv Machine Learning
Sep 15
When Can You Trust Your Synthetic Users? Diagnostics and Corrections for LLM Consumer Panels
arXiv:2609.13148v1 Announce Type: cross Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising $97\%$ cost reductions over traditional surveys. Yet aggregat...
arXiv AI
Jul 24
ImplicitBBQ: Benchmarking Implicit Bias in Large Language Models through Characteristic Based Cues
arXiv:2604. 01925v2 Announce Type: replace-cross Abstract: Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit biases when identity is conveyed indirectly.
arXiv AI
Jun 3
Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement
arXiv:2605. 11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables that can enter standard empirical designs.
arXiv AI
Jul 17
Innocuous-Seeming Data, Latent Ideology: Ideological Generalisation in Finetuned LLMs
arXiv:2607. 14888v1 Announce Type: cross Abstract: Finetuning language models on small, curated datasets is standard practice for adapting them to specific policies or domains.