Unlimited-OCR 🔥New OCR from Baidu huggingface.co/baidu/Unlimi... It can parse hundreds of pages in a single pass while maintaining stable speed. The key is R-SWA (Reference Sliding Window Attention), which keeps KV cache constant during decoding. 🏆 93% on OmniDocBench 📈 +6% ov…
Who's Who of AI
adinayakup.bsky.social
Why they matter
Researcher with public evidence across AI research.
- AI signals
- 2 past 30d
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- 1 distinct domains
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- 5h ago
AI Research @Hugging Face 🤗
Contributing to the Chinese ML community.
What they're sharing
baidu/Unlimited-OCR · Hugging Face huggingface.co
Paper page - Orca: The World is in Your Mind huggingface.co
GLM-5.2: Built for Long-Horizon Tasks huggingface.co
GLM-5.2 - a zai-org Collection huggingface.co
MiniMaxAI/MiniMax-M3 · Hugging Face huggingface.co
PP-OCRv6 - a PaddlePaddle Collection huggingface.co
LingBot-Video - a robbyant Collection huggingface.co
Hy3 - a tencent Collection huggingface.co
openbmb/MiniCPM5-2B · Hugging Face huggingface.co
Ling 3.0 Fin - a inclusionAI Collection huggingface.co
Agents-A1 - a InternScience Collection huggingface.co
LingBot-Vision - a robbyant Collection huggingface.co
Articles & links
BAAI just released the Orca paper 🔥 ( weights coming soon ) huggingface.co/papers/2606.... A Multimodal Latent World Model: it learns the world itself first, and text/images/actions are just different ways to read it out 💡
AI Weekly's analysis
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- Orca pretrains on 125K hours of video and 160M event annotations using a single Next-State-Prediction objective on a frozen Qwen3.5 backbone.
- Orca-4B averages 51.8 across MVBench, TemporalBench, 3DSRBench, and SWITCH, ahead of Qwen3.5-4B's 46.7 at the same size.
- On a real-robot out-of-distribution test Orca reports 36.6% versus π₀.5's 27.6%, despite using no action labels in pre-training.
Read full analysis →
Really cool to see the GLM 5.2 blog on Hugging Face 🔥 huggingface.co/blog/zai-org...
AI Weekly's analysis
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- GLM-5.2 scores 74.4% on FrontierSWE, within one point of Claude Opus 4.8's 75.1%, released under MIT license.
- The 753B model uses an IndexShare architecture that cuts per-token compute by 2.9x at 1M token context length.
- Z.AI claims GLM-5.2 is the highest-ranked open-source model across all three long-horizon coding benchmarks tested.
Read full analysis →
GLM 5.2 is here 🔥 huggingface.co/collections/... ✨ 753B - 1M context ✨ MIT license ✨ GLM IndexShare: reuses the indexer across layers, 2.9x fewer FLOPs/token at 1M ✨ AIME 2026: 99.2 (beats GPT-5.5, Claude Opus 4.8) ✨ vLLM / SGLang / Transformers supported
AI Weekly's analysis
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- Z.ai released GLM-5.2 on Hugging Face, a 753B-parameter open weights model under an MIT license with a 1M-token context window.
- An IndexShare design reuses the same indexer across every four sparse attention layers, reducing per-token FLOPs by 2.9x at 1M context length.
- Self-reported scores include 62.1 on SWE-bench Pro, 82.7 on Terminal Bench 2.1, 99.2 on AIME 2026, and 91.2 on GPQA-Diamond.
Read full analysis →
MiniMax-M3 just dropped 🔥 huggingface.co/MiniMaxAI/Mi... ✨ 428B / 23B active ✨ 1M context ✨ MiniMax Sparse Attention (MSA) And it’s not just weights! - paper: huggingface.co/papers/2606.... - kernel: huggingface.co/kernels/Mini... - Transformers support Love how this was relea…
PP-OCRv6 just released by Baidu huggingface.co/collections/... ✨ tiny 1.5M / small 7.7M / medium 34.5M ✨ 48+ languages ✨ Supports handwritten/printed/industrial/screen and card text ✨ Edge friendly deployment
LingBot-Video 🎬 MoE video model built for embodied AI from Ant group huggingface.co/collections/... - 30B/3B - Apache 2.0 - Trained on web videos + 70K hours of embodied data - Tops RBench: ahead of Cosmos3/Veo 3/Seedance 1.5 pro
AI Weekly's analysis
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- Robbyant released LingBot-Video, an Apache 2.0 mixture-of-experts video model with 30 billion parameters and 3 billion active per token.
- The model was trained on more than 70,000 hours of embodied data and rewards physical rationality alongside aesthetics and task completion.
- Self-reported RBench scores as of July 9, 2026 include 0.758 on quadruped, 0.689 on humanoid, and 0.620 overall.
Read full analysis →
Tencent just released HY3 🔥 huggingface.co/collections/... - 295B / 21B MoE , 256K context - Apache 2.0 - FP8 version included 👀 - Switchable reasoning: no think / low / high - Hallucinates half as often as before - Stable across agent frameworks
When everyone is releasing big models, OpenBMB keeps shipping small but strong one. Here is the latest one: MiniCPM5-2B 🔥 huggingface.co/openbmb/Mini... - Dense 2B - Full data pipeline open as well: web, code, agent, RL - 131 context - Apache 2.0
Ling-3.0-flash-Fin 💰 A finance tuned build of Ling-3.0-flash from Ant Group huggingface.co/collections/... - 124B/ 5.1B active - 256K context - MIT license - Finance native agent workflows - Already being quantized for llama.cpp
Agents-A1 🤖🔬 New agentic model from Shanghai AI Lab, InternScience team huggingface.co/collections/... - 35B MoE (built on Qwen3.5-35B-A3B) - Apache 2.0 - 256K context - Trained for long-horizon agent work - Includes quantized variants
LingBot Vision 👀🤖 A self-supervised vision backbone family for dense spatial perception from Ant Group huggingface.co/collections/...
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