2 papers
cs.LG2026
The Significance of Style Diversity in Annotation-Free Synthetic Data Generation
Zahra Abbasiantaeb, Zeno Belligoli, Omar Essam +1
Generating high-utility synthetic data for intent classification typically requires human-annotated seed data, which is often unavailable in fast-paced industrial settings. In this…
cs.CL2025
Controlling Summarization Length Through EOS Token Weighting
Zeno Belligoli, Emmanouil Stergiadis, Eran Fainman +1
Controlling the length of generated text can be crucial in various text-generation tasks, including summarization. Existing methods often require complex model alterations, limitin…