2 papers
cs.IR2026
Aligning Dense Retrievers with LLM Utility via Distillation
Rajinder Sandhu, Di Mu, Cheng Chang +4
Dense vector retrieval is the practical backbone of Retrieval- Augmented Generation (RAG), but similarity search can suffer from precision limitations. Conversely, utility-based ap…
cs.LG2026
TabDPT: Scaling Tabular Foundation Models on Real Data
Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh +7
Tabular data is one of the most ubiquitous sources of information worldwide, spanning a wide variety of domains. This inherent heterogeneity has slowed the development of Tabular F…