HPD-Parsing reaches 94.91% on OmniDocBench v1.6 with 4,752 TPS throughput
pmttyji · reddit · 2026-07-23
HPD-Parsing proposes a hierarchical parallel decoding approach for document parsing.
The model splits work between a global layout branch and localized content branches, then further reduces decoding with Progressive Multi-Token Prediction and shared-prefix KV cache reuse. According to the post, the 1B model reaches 94.91% on OmniDocBench v1.6 and peaks at 4,752 TPS, which the authors say is 2.62× faster than the previous best parser and 3.06× faster than its autoregressive baseline.
More from Research
- Causal-only attention for non-generative tasks is wasteful, argues HF engineer — antoine_chaffin · 2026-09-11
- Catholic University of Chile researcher: scaling AI feedback is key to sustainable medical education — julianvarascom · 2026-09-11
- Nature paper images cellular activity across all organs, revealing body-wide circuits — arjunrajlab · 2026-09-11
- SignNet 1M Dataset Released for Sign Language Research — ducha_aiki · 2026-09-11
- ECCV26 Oral: Flow Matching Enables Single-Stage Multi-View Point Cloud Registration — ducha_aiki · 2026-09-11
- InFlux++ Method Released — ducha_aiki · 2026-09-11