The strangerzonehf [HF] Community / Organization Page, which is maintained by me, has reached the Top 10 Developer Pages ranking at 6th place, contributing 3.4% in the calendar cycle from August 2024 to August 2025. It is also the only South Asia / Indian page in the list. I could not be more proud to be doing things for the community. ❤️🤗
Today, we announce Mistral 3, the next generation of Mistral models. Mistral 3 includes three state-of-the-art small, dense models (14B, 8B, and 3B) and Mistral Large 3 – our most capable model to date – a sparse mixture-of-experts trained with 41B active and 675B total parameters.
All models are released under the Apache 2.0 license.
9 Recent advances in Multi-Agent Systems (all open-source)
The idea to split tasks across multiple agents instead of relying on one universal agent is now seen as one of the most effective ways to build an AI stack. Concepts like “agent swarms” were highlighted at the AI Engineer Code Summit in NYC (Nov 20–21) as the winning architecture. And this trend is not only about coding and software. It applies across all AI domains.
So here is some recent research that helps keep multi-agent systems (MAS) better and up-to-date:
1. LatentMAS → Latent Collaboration in Multi-Agent Systems (2511.20639) AI agents share their hidden "thoughts" directly in latent space instead of talking through text. This makes collaboration and reasoning way faster and accurate (no extra training needed)
2. Puppeteer → Multi-Agent Collaboration via Evolving Orchestration (2505.19591) Uses a “puppeteer” LLM that dynamically decides which agents (“puppets”) to call and in what order. By learning this orchestration with reinforcement learning (RL), the system solves complex tasks more efficiently and with fewer compute costs
3. MADD → MADD: Multi-Agent Drug Discovery Orchestra (2511.08217) A MAS with 4 agents for drug discovery. It lets researchers describe a drug discovery task in plain language. Then MADD automatically builds and runs the full hit-identification pipeline, making AI-driven drug design a simple end-to-end workflow
4. Multi-Agent Tool-Integrated Policy Optimization (MATPO) → Multi-Agent Tool-Integrated Policy Optimization (2510.04678) Lets one LLM act as multiple agents (like a planner and a worker) by using different prompts and training them together with RL. So you get the benefits of a multi-agent system without needing multiple models
Exciting updates to the Wikipedia Monthly dataset for November! 🚀
・ Fixed a bug to remove infobox leftovers and other wiki markers such as __TOC__ ・ New python package https://pypi.org/project/wikisets: a dataset builder with efficient sampling so you can combine the languages you want seamlessly for any date (ideal for pretraining data but works for any purpose) ・ Moved the pipeline to a large server. Much higher costs but with better reliability and predictability (let me know if you'd like to sponsor this!). ・ Dataset sizes are unfortunately missing for this month due to shenanigans with the migration, but should be back in December's update.
Need Help Getting arXiv Endorsement for My AI Research Paper
Hi everyone, I hope you're doing well. I’m trying to publish my new AI research paper on arXiv under the cs.AI category, but I currently need an endorser who is already authorized for cs.AI submissions.
If anyone here is registered as a cs.AI endorser and is willing to help, I would truly appreciate it.
Here is the official arXiv endorsement request link:
My research: It’s part of the AetherMind project — a self-reflective NLI reasoning system inspired by human cognitive consistency and used also in Alzheimer’s research. If needed, I can share the abstract or full PDF.
I am now being charged for paused and unstarted spaces out of the blue. I think this is it, folks. o7
The unstarted spaces I can get behind. I would've appreciated a warning email first, but whatever. However, every time I restart the active usage goes up, despite all of my spaces being moved to CPU (free), and being paused.
Introducing the japanese-trending-words dataset: a dataset consisting 593 words from Japan’s annual trending word rankings (流行語大賞) from 2006-2025. This dataset provides the top 30 words from each year and its meaning in Japanese and english. This resource is awesome for NLP tasks understanding recent Japanese culture and history.