arXiv Computation and Language
3d ago

GAVAGAI: Referential Alignment for Infant-Scale Vision-Language Models via Balanced Optimal Transport

The paper introduces GAVAGAI, a method that adds a referential alignment variable to vision‑language models by solving a small assignment problem via entropic optimal transport. By allowing words to be assigned to a special NOTHING column and enforcing a capacity constraint on regions, the approach improves word‑to‑picture accuracy and localization on the SAYCam infant video corpus. Experiments show that the alignment loss boosts performance over a standard next‑token captioning baseline, especially under high non‑reference rates.

By Rajdeep Pal, Jotiraditya Banerjee, Saptarshi Pani