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Running on Zero
Running on Zero
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Yesterday
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Links to paper, project page, code, model and dataset; official BibTeX Running
hanhaonan02 +1: Claude Fable 5.1Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>02e9784
2 days ago
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Examples are five RAP-150 benchmark cases reproduced from their exact prompts
hanhaonan02 +1: Claude Fable 5.1- examples/<case>/: paper.pdf, our poster (PNG + self-contained HTML), prompt.json (exact test prompt), thumbnails/ and full-resolution assets/; meta.json carries the exact instruction, layout spec and canvas size - picking a card fills PDF, instruction, spec and canvas; Generate feeds the stored prompt verbatim when the PDF, instruction and spec are unchanged (matched by PDF hash), otherwise the regular parser runs - canvas accepts exact WxH sizes; replaced NExT-GPT / ConforMix with Deep Ensembles (ICML 2025) and Theory of Mind (ICLR 2023) Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>9b03fbd
3 days ago
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Point to renamed model repo RAP-Qwen3.8-27B-RL
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5 days ago
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Author line: drop bare e-mail domains, attach combining marks to the following letter
hanhaonan02 +1: Claude Fable 5.1Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>f1b7085 -
Take the author line from the first page, not PDF metadata
hanhaonan02 +1: Claude Fable 5.1Without an authors line the model invented author names on a Space-generated poster. Lines between the title block and the abstract are used; e-mails and stray combining marks removed. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>96e4fd5 -
Adaptive ZeroGPU step length with a quota explanation
hanhaonan02 +1: Claude Fable 5.1- Ask for a 600 s xlarge step first (one weight transfer, most posters finish in one step) and fall back to 300/120/60 s when ZeroGPU answers 'larger than the maximum allowed'. - Generation budget derives from the step length; status shows the step length. - Quota hint on failures: 27B BF16 needs the full GPU (2x quota), ~15-25 min per poster; PRO 40 min, free 5 min, anonymous 2 min per day. README says the same. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>4b73edf -
One request per ZeroGPU step; keep small-caps titles intact
hanhaonan02 +1: Claude Fable 5.1- The ZeroGPU proxy token is bound to the HTTP request; parsing plus several 120 s steps in one request failed with 'Expired ZeroGPU proxy token'. Generate is now a chain: /analyze (CPU) then up to 10 chained /step events, one GPU step each; Continue re-enters the chain. - Title extraction joins touching spans and takes whole title lines, so ICLR small-caps titles no longer collapse to initials; falls back to PDF metadata when the result looks broken. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>033094c -
Accept any colour-picker format for the accent; replace examples with five stronger test-set posters
hanhaonan02 +1: Claude Fable 5.1- normalize_accent(): #RGB/#RRGGBB/rgb()/rgba()/hsl() -> #RRGGBB, default on failure (the picker could send rgba(...) and the old check raised 'Choose an accent color in #RRGGBB format') - Examples: MAESTRO (ICLR 2023), Gradient Leakage (ICLR 2022), Humanoid Motion (ICLR 2024), NExT-GPT (ICML 2024), ConforMix (NeurIPS 2025), each with PDF, PNG and self-contained HTML Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>77e6466
6 days ago
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Redesign demo UI, add five curated examples, trim README
hanhaonan02 +1: Claude Fable 5.1- New compact layout: hero, inputs left, poster + downloads right, example gallery - Generation chains ZeroGPU steps automatically; downloads only appear when ready - Five examples (NeurIPS 2022/2024, ICML 2022 x2, ICLR 2025) from the released checkpoint - Remove placeholder example; LFS for png/pdf/zip; shorter README Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>10726af -
Publish-ready PDF to poster demo with validated BF16 example and safe continuation
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Add training-aligned PDF parser, safe rendering and resumable poster generation
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Private BF16 ZeroGPU model bring-up
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initial commit
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