243 Mp4 Apr 2026

: Critically examines gender biases in reference letters generated by LLMs like GPT.

In academic circles, "243" often refers to a paper's identifier in a specific conference track. Depending on your interest, you might also be looking for: 243 mp4

: Uses social science-inspired evaluation methods to track bias propagation across language style and lexical content. Resources : Read the Full Paper (PDF) Watch the Presentation (243.mp4) (Direct Video Link) Other Related Papers (Index 243) : Critically examines gender biases in reference letters

This 2023 paper by Wan et al. investigates how large language models (LLMs) may perpetuate social biases when writing recommendation letters. It is highly regarded for its systematic approach to examining language style and lexical content. Resources : Read the Full Paper (PDF) Watch

: "A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation" – A 2023 paper addressing gender bias specifically in machine translation.