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.CL2026
uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking
Simon Lupart, Kidist Amde Mekonnen, Zahra Abbasiantaeb +1
This report describes our participation in SemEval-2026 Task 8 on multi-turn retrieval and question answering. The task evaluates conversational systems across four domains (financ…