4 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
NEvo: Neural-Guided Evolutionary Video Synthesis for Dynamic Visual Selectivity
Yingtian Tang, Sogand Salehi, Ming Zhou +3
The human brain processes dynamic visual input through hierarchically organized, functionally specialized regions. While recent in silico brain encoding models can synthesize optim…
MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities
Mingqiao Ye, Zhaochong An, Zhitong Gao +11
Any-to-any models predict any modality from any combination of others within a single network, a formulation used in multimodal vision and vision-language models, and increasingly…
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
Kunal Pratap Singh, Ali Garjani, Rishubh Singh +6
Cross-modal learning, i.e., learning to predict one modality from another, is a fundamental mechanism for self-supervision via leveraging multimodality. Many practical applications…
(1D) Ordered Tokens Enable Efficient Test-Time Search
Zhitong Gao, Parham Rezaei, Ali Cy +7
Tokenization is a key component of autoregressive (AR) generative models, converting raw data into more manageable units for modeling. Commonly, tokens describe local information,…
VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
Andrei Atanov, Jesse Allardice, Roman Bachmann +6
Visual tokenizers map high-dimensional raw pixels into a compressed representation for downstream modeling. Beyond compression, tokenizers dictate what information is preserved and…