5 papers
SJD-SV: Speculative Jacobi Decoding with Semantics Verification for Autoregressive Image Generation
Baoquan Zhang, Bingqi Shan, Shihao Fang +3
Speculative Jacobi Decoding (SJD) is an important approach for accelerating autoregressive image generation. Although SJD has shown superior performance, recent studies point out t…
Accelerating Visual On-Policy Distillation with Batched Speculative Jacobi Rollouts
Bingqi Shan, Zhehao Yu, Kenhong Lin +1
Visual on-policy distillation (OPD) improves the training of compact visual autoregressive models by learning from trajectories generated by the current student. However, these onl…
SJD-VP: Speculative Jacobi Decoding with Verification Prediction for Autoregressive Image Generation
Bingqi Shan, Baoquan Zhang, Xiaochen Qi +3
Speculative Jacobi Decoding (SJD) has emerged as a promising method for accelerating autoregressive image generation. Despite its potential, existing SJD approaches often suffer fr…
SJD-PV: Speculative Jacobi Decoding with Phrase Verification for Autoregressive Image Generation
Zhehao Yu, Baoquan Zhang, Bingqi Shan +5
Autoregressive (AR) image models have recently demonstrated remarkable generative capability, but their sequential nature results in significant inference latency. Existing trainin…
Prototype Optimization with Neural ODE for Few-Shot Learning
Baoquan Zhang, Shanshan Feng, Bingqi Shan +3
Few-Shot Learning (FSL) is a challenging task, which aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a…