Chenguo Lin
1 indexed paper
Recent (6 mo)
1With code
0Influential cites
0Benchmarked
0Publications per year
126
Top categories
Vision×1
Frequent co-authors
Research Timeline
2026
GEAR: Guided End-to-End AutoRegression for Image Synthesis
This paper introduces GEAR, a method for training a vector-quantized tokenizer and an autoregressive generator jointly and end-to-end, resolving the issue of non-differentiable VQ indices.
Highlighted terms show continued research focus across papers
Papers
cs.CVEmpiricalRecentJun 30, 2026
GEAR: Guided End-to-End AutoRegression for Image Synthesis
Bin Lin, Zheyuan Liu, Chenguo Lin, Sixiang Chen +7 more
This paper introduces GEAR, a method for training a vector-quantized tokenizer and an autoregressive generator jointly and end-to-end, resolving the issue of non-differentiable VQ indices.
View →