In the news
Diffusion Drafts, AR Verifies: Accelerating Document OCR with Self-Speculative Decoding
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- GravityOCR combines diffusion-based parallel drafting with autoregressive verification to accelerate document OCR, achieving 3.94x speedup on crops and 1.32x end-to-end speedup.
- Why it matters
- Matters for engineers building document processing systems where OCR inference speed is a bottleneck and accuracy on structured text extraction is critical.
- Watch out
- Model performance remains slightly below the baseline GLM-OCR score of 95.48, and speedups vary significantly between isolated crops and full page processing.
- language model
- speculative
- inference
- token
The patterns behind this
- Speculative & Parallel Tool Execution
- Process Reward Models & Verifier-Guided Search
- Chain of Verification (CoVe)
Each one covers how the technique works, when it earns its cost, and where it breaks.
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