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Collin McCarthy

3 accepted papers

2026

RADIO1D: Elastic Representations for Condensed Vision Modeling

ICML 2026poster

This paper challenges the assumption that vision-language models (VLMs) require fixed patch-based 2D vision features. Analyzing fine-tuned vision encoders, we find that representations become increasingly abstract and less spatially coherent during VLM training. Notably, models trained with image-te…

Cited by 0SourceScholar
2026

Scaling Parallel Sequence Models to Vision Foundation Models

CVPR 2026

Scaling vision foundation models is constrained by the quadratic complexity of self-attention. Although subquadratic attention alternatives like linear attention variants and state-space models successfully reduce the model complexity, they typically serialize images into 1D token sequences, comprom

Cited by 0SourceScholar
2025

GSPN-2: Efficient Parallel Sequence Modeling

NeurIPS 2025poster

Efficient vision transformer remains a bottleneck for high-resolution images and long-video related real-world applications. Generalized Spatial Propagation Network (GSPN) \cite{wang2025parallel} addresses this by replacing quadratic self-attention with a line-scan propagation scheme, bringing the c…

Cited by 0SourceScholar