11 citations · 17 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning Representations to Guide Pixel Diffusion Transformers
Zihao Pan, Mengting Chen, Cheng Shi +6
Visual representations are largely developed for understanding, yet what makes them useful for generation remains unclear. We study this question in pixel diffusion transformers an…
Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models
Aiwei Liu, Cheng Shi, Chuhan Wu +44
Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining…
WeaveTime: Stream from Earlier Frames into Emergent Memory in VideoLLMs
Yulin Zhang, Cheng Shi, Sibei Yang
Recent advances in Multimodal Large Language Models have greatly improved visual understanding and reasoning, yet their quadratic attention and offline training protocols make them…
Vision Transformers Need More Than Registers
Cheng Shi, Yizhou Yu, Sibei Yang
Vision Transformers (ViTs), when pre-trained on large-scale data, provide general-purpose representations for diverse downstream tasks. However, artifacts in ViTs are widely observ…