He Said, She Said: Gender in the ACL Anthology

``He Said She Said'' ― a Male/Female Corpus of Polish

Gender differences in language use have long been of interest in linguistics. The task of automatic gender attribution has been considered in computational linguistics as well. Most research of this type is done using (u…

Measuring Political Bias in Large Language Models: What Is Said and How It Is Said

We propose to measure political bias in LLMs by analyzing both the content and style of their generated content regarding political issues. Existing benchmarks and measures focus on gender and racial biases. However, pol…

Women Are Beautiful, Men Are Leaders: Gender Stereotypes in Machine Translation and Language Modeling

We present GEST -- a new manually created dataset designed to measure gender-stereotypical reasoning in language models and machine translation systems. GEST contains samples for 16 gender stereotypes about men and women…

Extractive email thread summarization: Can we do better than He Said She Said?

SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding

Diffusion large language models (DLLMs) enable non-autoregressive generation by iteratively denoising corrupted token sequences with bidirectional context. Despite their ability to update multiple positions in parallel, …