3 papers
cs.CV2024
Efficient Vision-Language Models by Summarizing Visual Tokens into Compact Registers
Yuxin Wen, Qingqing Cao, Qichen Fu +2
Recent advancements in vision-language models (VLMs) have expanded their potential for real-world applications, enabling these models to perform complex reasoning on images. In the…
cs.CV2024
CtrlSynth: Controllable Image Text Synthesis for Data-Efficient Multimodal Learning
Qingqing Cao, Mahyar Najibi, Sachin Mehta
Pretraining robust vision or multimodal foundation models (e.g., CLIP) relies on large-scale datasets that may be noisy, potentially misaligned, and have long-tail distributions. P…
cs.CL2024
KV Prediction for Improved Time to First Token
Maxwell Horton, Qingqing Cao, Chenfan Sun +4
Inference with transformer-based language models begins with a prompt processing step. In this step, the model generates the first output token and stores the KV cache needed for f…