MonkeyOCRv2: A Visual-Text Foundation Model for Document AI
Paper β’ 2607.11562 β’ Published β’ 15
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nielsrΒ
submitted a
paper to Daily Papers 5 days ago
nielsrΒ
submitted a
paper to Daily Papers 6 days ago
nielsrΒ
submitted 2
papers to Daily Papers 11 days ago
GeorgeBredisΒ
submitted a
paper to Daily Papers 12 days ago
nielsrΒ
submitted 2
papers to Daily Papers 12 days ago
nielsrΒ
submitted a
paper to Daily Papers 13 days ago
DongfuJiangΒ
authored 2
papers 14 days ago
Post
2058
You can explore and try my Agentic Space Factory:
fffiloni/agentic-space-factory-UI-public
Be kind π€
fffiloni/agentic-space-factory-UI-public
Be kind π€
Post
1805
I made a Hugging Face Space for SCAIL-2 π€
Reference character + driving motion β animated result.
A simple demo to explore the paperβs core workflow with curated examples.
π fffiloni/SCAIL-2
Reference character + driving motion β animated result.
A simple demo to explore the paperβs core workflow with curated examples.
π fffiloni/SCAIL-2
- 1 reply
Post
808
β±οΈ Built a small Space for Visual Chronometer / Pulse of Motion.
Upload a video and estimate its Physical FPS: the frame rate implied by visual motion, independent of metadata.
Useful to inspect βchronometric hallucinationβ in generated videos: clips that look smooth, but move with the wrong physical time scale.
Try it here: fffiloni/Pulse-of-Motion
Upload a video and estimate its Physical FPS: the frame rate implied by visual motion, independent of metadata.
Useful to inspect βchronometric hallucinationβ in generated videos: clips that look smooth, but move with the wrong physical time scale.
Try it here: fffiloni/Pulse-of-Motion
- 1 reply
PrabhjotschughΒ
authored 4
papers 21 days ago
Not Truly Multilingual: Script Consistency as a Missing Dimension in VLM Evaluation
Paper β’ 2606.17188 β’ Published β’ 1
FirstPass: Grounding AI Scientific Judgment in Multi-Round Editorial Outcomes
Paper β’ 2606.20769 β’ Published β’ 1
Beyond 'One Language, One Script': Quantifying Orthographic Bias in Multilingual VLMs with PuMVR
Paper β’ 2606.20770 β’ Published β’ 1
AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion
Paper β’ 2605.26130 β’ Published β’ 1
Post
1562
A few weeks ago, @victor opened the door: coding agents can now ship Hugging Face Spaces autonomously.
I pulled on that thread.
As someone who builds and ships Gradio demos regularly, I didnβt just want to reproduce the loop. I wanted to see what happens when that loop is plugged into the whole Hugging Face stack.
The interesting part is not only that an agent can ship a Space.
Itβs what happens when Space generation becomes a first-class Hugging Face workflow.
That became Agentic Space Factory.
More soon. π€
I pulled on that thread.
As someone who builds and ships Gradio demos regularly, I didnβt just want to reproduce the loop. I wanted to see what happens when that loop is plugged into the whole Hugging Face stack.
The interesting part is not only that an agent can ship a Space.
Itβs what happens when Space generation becomes a first-class Hugging Face workflow.
That became Agentic Space Factory.
More soon. π€
- 1 reply
nielsrΒ
submitted a
paper to Daily Papers about 1 month ago
Post
4526
We trained an open-source Mythos like cybersecurity LLM for the Build Small Hackathon meet OpenMythos
Trained in two stages: SFT on ~1.84K filtered ArXiv cs.CR papers + real CVE data, then RLVR using paired with past vulnerabilities GitHub repos with a verifier model checking outputs against ground truth.
Trained on: H100s from Modal
The RLVR stage made the biggest difference responses got more precise and less prone to confusing similar vulnerability classes.
Everything is open:
π€ Demo β build-small-hackathon/OpenMythos
π§ Model β build-small-hackathon/OpenMythos
π¦ CVE Dataset β build-small-hackathon/CVE_Vulnerailities_Detailed
π ArXiv Dataset β himanshu17HF/ArvixImport-Filtered-Final
Try it out and let us know where it breaks π
Trained in two stages: SFT on ~1.84K filtered ArXiv cs.CR papers + real CVE data, then RLVR using paired with past vulnerabilities GitHub repos with a verifier model checking outputs against ground truth.
Trained on: H100s from Modal
The RLVR stage made the biggest difference responses got more precise and less prone to confusing similar vulnerability classes.
Everything is open:
π€ Demo β build-small-hackathon/OpenMythos
π§ Model β build-small-hackathon/OpenMythos
π¦ CVE Dataset β build-small-hackathon/CVE_Vulnerailities_Detailed
π ArXiv Dataset β himanshu17HF/ArvixImport-Filtered-Final
Try it out and let us know where it breaks π
- 2 replies