Aditya Tanna

Tabular foundation models can achieve state-of-the-art in-context learning by selectively activating feature-specific experts, outperforming dense models on challenging datasets.

Clinical QA models can now achieve substantial gains by leveraging a composite reward that fuses external ontology concept overlap with an LLM judge, outperforming SFT and capturing nuanced factual correctness.