Papers with racial descriptors

2 papers
Thesis Proposal: Auditing and Mitigating Demographic Bias in Multi-Stage Retrieval Systems for Criminal Justice Applications (2026.acl-srw)

Copied to clipboard

Challenge: racial descriptors alter embedding similarity scores and retrieval rankings, a new study shows . rife-specific biases can displace relevant records outside top-10 results, the study concludes .
Approach: They propose to detect, measure, and mitigate racial bias in NLP systems deployed in criminal justice contexts . they propose to develop and evaluate debiasing techniques, validate synthetic findings on authentic law enforcement data .
Outcome: The proposed research examines how bias propagates across retrieval pipelines . it shows that racial descriptors alter embedding similarity scores and retrieval rankings .
Measuring and Mitigating Racial Bias in Embedding Models: A Comparative Study for Law Enforcement Retrieval (2026.acl-industry)

Copied to clipboard

Challenge: Embedding models are often used for semantic retrieval in high-stakes domains such as law enforcement . racial descriptors affect similarity scores and retrieval rankings for semantically identical crime incidents .
Approach: They propose to use racial descriptors to measure r&d bias in embedding models . they compute similarity scores between crime incidents and simple law enforcement queries .
Outcome: The proposed methods show that racial descriptors affect similarity scores and retrieval rankings for semantically identical crime incidents.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations