We’re sharing model checkpoints, an evaluation benchmark, human body training data, and inference code with the community to support creative applications in fields like robotics, interactive media, science, sports medicine, and beyond. SAM 3D Body:
OPEN SOURCE
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alphaXiv Bridges AI Research-to-Practice Divide with Integrated Platform
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alphaXiv is solving this by bridging the AI research-to-practice divide. We’re bringing together papers, benchmarks, and implementations into a single platform that makes it seamless for any AI practitioner to discover and build on top of the latest research.
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Siddharth’s Major Contributions to Flowise AI Open Source
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Thank you @aibysid for all these awesome PRs! Open source ftw 🙌 Siddharth Chauhan (@aibysid) 🚀 I’ve Been Hacking on @FlowiseAI Lately — Here’s What I’ve Built 👇 So over the last few weeks I’ve gone down a bit of a Flowise rabbit hole… in a good way 😄 I ended up opening a bunch of PRs to the project and thought I’d share what I actually did. If you haven’t used Flowise: it’s basically a super-nice visual builder for AI agents. Drag, drop, connect nodes, and boom — you’ve got a working LLM workflow. 🔧 What I’ve Been Fixing & Adding 🗑️ 1. AgentFlow list didn’t refresh after deleting Small bug, annoying experience. Fixed it so when you delete an AgentFlow, the UI instantly updates. No more manual refreshes. Tiny change, but feels way better. 🖼️ 2. Added image upload support to the ChatOpenRouter node Wanted multimodal flows inside Flowise — so now you can just drop images into the node. Opens up tons of cool use-cases. 🧾 3. Agent node can now output structured JSON Earlier, responses were mostly text. I added proper structured JSON output so people can build cleaner automations or connect flows to other tools without parsing headaches. 🚨 4. Fixed inconsistent status codes Some API calls returned weird/inconsistent errors for invalid chatflow IDs. Cleaned that up so failures are predictable and easier to handle. 🤖 5. Improved support for Hugging Face inference providers Made Flowise a bit more flexible by making model provider integrations work more smoothly with the HF inference API. 📝 6. Added image loader w/ OCR support (multiple providers!) One of my favourites — Flowise can now take in images and run OCR through different providers. Super useful for docs, receipts, screenshots, all that stuff. 🤔 Why I Did All This Honestly, I just started exploring the codebase and found small areas that could be improved. And once you make 1 PR, you kinda get hooked. Plus: Multi-modal workflows are the future JSON output makes everything easier A good user experience is basically 50% of why people love a tool Flowise is growing fast, so contributing early is fun 🎯 What I Learned Messing With Flowise OSS PRs teach you WAY more than tutorials ever will “Small things” like UI refresh bugs make a big difference Multi-modal + agent workflows get tricky behind the scenes Consistent API behavior is underrated Flowise’s architecture is actually pretty clean once you get the hang of it 🔮 What’s Next I’m planning to pick up stuff around permissions, workspaces, and maybe build some sample flows showing image-upload → OCR → agent reasoning → structured output. Also thinking of writing a guide for beginners who want to contribute. 🙌 If You’re Into AI Agents or Flowise Hit me up, or drop into the repo. There’s a lot of cool stuff happening and it’s a great project if you want to get into open-source around LLMs. Here is is list of my PRs: github.com/FlowiseAI/Flowise… — https://nitter.net/aibysid/status/1991120542594949189#m
→ View original post on X — @flowiseai, 2025-11-19 12:48 UTC
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Chinese LLMs Making GenAI Affordable and Accessible Globally
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Decent-quality LLMs from China are really helping make GenAI affordable and accessible to the world through open source. Pursuing AGI with close models might be a winner-take-all game for U.S. big techs, but making AI more open will benefit researchers, students, entrepreneurs, and hobbyists in building AI that works for them. More in this @BloombergAsia interview: bloomberg.com/news/videos/20…
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Gemini 3 Deep Think scores 41% on HLE
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BREAKING : Gemini 3 Deep Think gets 41% on HLE and 45.1% on ARC_AGI-2! "In testing, Gemini 3 Deep Think outperforms Gemini 3 Pro’s already impressive performance on Humanity’s Last Exam and GPQA Diamond."
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Gemini 3 Pro Benchmarks Break Records
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Gemini 3 Pro benchmarks are wild – Humanity’s Last Exam: 37.5%
– ARC-AGI-2: 31.1% True SOTA -
Firecrawl: Open Source AI Web Scraping Tool
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Github Repo: https://
github.com/firecrawl/fire
crawl
… Check it out here: -

GPT-5.1 tops ARC AGI 2 benchmark
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GPT-5.1 Thinking High from OpenAI claims a top spot on ARC AGI 2 benchmark and dethrones Grok 4. Was GPT-5.1 undehyped?
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AI Engineering Toolkit: Open Source Resources for Developers
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Link to the GitHub repo (2K+ Github Stars): https://
github.com/Sumanth077/ai-
engineering-toolkit
… Feel free to add new tools and libraries and contribute! -

100+ LLM Libraries and Frameworks for AI Engineering
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AI Engineering Toolkit! I have curated a list of 100+ LLM libraries and frameworks for training, fine-tuning, building, evaluating, deploying, RAG, and AI Agents. Categories of LLM Libraries include: • Vector Databases – Store and retrieve embeddings efficiently.
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