manueltonneau/llm-demographic-cues
Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias Model responses and derived tables for the EMNLP 2026 paper. Analysis code: https://github.com/manueltonneau/llm-demographic-cues Manuel Tonneau, Neil K. R. Sehgal, Niyati Malhotra, Sharif Kazemi, Victor Orozco-Olvera, Ana María Muñoz Boudet, Lakshmi Subramanian, Samuel P. Fraiberger, Sharath Chandra Guntuku, Valentin Hofmann. Different Demographic Cues Yield Inconsistent Conclusions… See the full description on the dataset page: https://huggingface.co/datasets/manueltonneau/llm-demographic-cues.
State the license and the upstream corpora's terms explicitly
Fix the master-table rebuild instructions: both caches ship with the data
Cite the arXiv preprint; update paths for the reorganized code repo
Add asl_cache (average sentence length per prompt), needed by build_masters.py
Add files using upload-large-folder tool
Add files using upload-large-folder tool
Add files using upload-large-folder tool
Add files using upload-large-folder tool
initial commit
