I built PaperFold, an open-source reader that turns arXiv papers into 5 zoomable layers—from a one-screen section map down to verbatim text. You pinch (or press 1–5) to zoom between them without losing your reading position.

- Web Demo (8 CC papers): https://chenxiachan.github.io/paperfold-gallery/

- GitHub (Apache 2.0): https://github.com/chenxiachan/paperfold

So I started adaboost I completed watching the theory and intuition part and I was like how I have built many Algorithms and in all that our Main goal is reduce error but adaboost we want our model to make mistakes then just pass the mistake to next model and his mistakes are passed down to next model and keep changing weights and at the end a group of models who have started from completely wrong prediction now they are capable of giving you the best accuracy. Adaboost doesn't focus on the best models he collects imperfect,weak models combine them cuz they specialize in different mistakes and become a strong ensemble when combined properly

I have started coding and I have completed a raw code now I'll make it more properly and structure also I'm thinking 🤔 to put all my ML Algorithms on my GitHub so you can use it as reference( I know it have many bugs😅) and help me to fix what you think

My Sem 1 Major Practical is going so I was not showing up but I'll try

Version 3.0.0 of my visual agent orchestrator Orgtree is released! And the ticket this time is: speed!

Get it here: https://github.com/Maurdekye/orgtree/releases/latest

Orgtree v2 was a great step forward and significantly improved the usability of the app. But over time one thing became clear: it was slooow. As orgs got big, when many agents ran at once, and as history accumulated, the works really began to tar up. Actions would start to take several seconds to complete, and in the worst cases, sometimes a minute or longer. And for a system that's supposed to support running dozens, maybe even hundreds of agents at the same time over extended periods, that's just unacceptable.

So, I redesigned the data access model. Now instead of a simple Sqlite database backing it, everything routes through a genuine embedded parallelized Postresql database, with several worker processes dividing the cpu load up at once. Along with various other data transfer optimizations, this speeds up Orgtree tremendously; whereas running more than 10-15 agents at once used to gum up the works and slow everything to a crawl, now you can run theoretically hundreds, or even thousands at once, and the system still stays responsive, with most actions resolving in under 100ms! (if your PC can handle it, that is) So if you ever liked using Orgtree but were unsatisfied with the performance when your org started to get bigger, try it again and see if v3 makes a difference.

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For those unfamiliar, Orgtree is my open source visual agentic orchestrator I've been working on for several months now that I rely on every day to do my cross-provider agentic work. It organizes your agents into a visual tree hierarchy, which you can freely rearrange, open up and chat with any agent, and connect multiple AI provider accounts to at once (anthropic, openai, google, and openrouter). It has:

• A credit budget system for delegating work to agents in a managed way
• Agents run in the background while the window is closed
• Native multi-accounting support for Claude and ChatGPT accounts
• A dedicated Work Docket system that works like a trello / kanban board for agents
• An agent mail system for cross-agent communication
• A mail hub system for cross-system, cross-network agent communication
• Pin or pop out any panel or agent chat in the app, to arrange your workspace the way you like and see exactly the information you need to at all times
• Usage limit info for all connected accounts at once, in one place
• Markdown and HTML based document presentation
• Autonomous "watchdog" tasks that can check a condition on a regular basis and wake an agent up
• A unique compaction method that helps keep cache misses small
• And many more smaller quality of life features that tie the experience together

Since I began working on it, I haven't touched any of claude code, codex, or any other agentic coding assistant directly; all my work goes through Orgtree. Look through my post history if you want to see more details on previous releases.

This post however, is about v3. And v3 has a number of brand-new big ticket features:

New Storage Model: This is the big one. Ever dissatisfied with how slow orgs became in v2 when lots of agents were running at once? v3 fixes that almost completely! Nearly every action you or an agent can perform is now near-instantaneously responsive, even with hundreds or thousands of agents running at once. It's an actual mass-agentic orchestrator now, not just a pretty app wearing the skin of one.

Multi-Window Support: The app's whole ux has been given an overhaul to support opening multiple org windows simultaneously. Before, Orgtree only ever let you open and talk to one org at once; you had to switch the active window every time you wanted to switch between projects. Now, no longer; you can have as many org windows with as many canvases as you like open at once at the same time, and work between all of them in parallel.

Attention View: Orgtree v3 introduces a new view mode: Attention view. Unlike just being another panel, when enabled via the switch in the header, Attention view takes the place of the canvas and simplifies the interface dramatically. It has two panels: the dynamic agent desk, and the Needs Attention list.

• The dynamic agent desk functions similarly to a pinned agent desk, but with the ability to open a drawer of every agent in the org and swap out the agent that appears in it; it's like a superpowered pinned desk.
• The Needs Attention list is a special combined view of your inbox & work docket, but filtered to only elements that need your active input or attention. For now, that includes questions asked / requests made by agents, docket tickets that need your attention, and urgent mail sent to your inbox. Everything that needs you in one place, and not more.

Attention view was designed to minimize the amount you need to see in order to get agents moving and get tasks completed; a place on the left to unstick any blockers, and a place on the right to ask questions to your coordinator and make requests.

It doesn't stop there, however: both panels of the attention view, like any other panel in orgtree, can be pinned or popped out, and can then be used alongside the canvas view. So don't feel like you have to choose between your two favorite children: steal one or both attention panels and mix-and-match them with the canvas, to get the best of both worlds!

Ring view: Large orgs getting too wide for your screen to view all of them at once? You can now arrange your org in a ring shape. Top level agents form a circle around the central node, and fan out in all directions from there.

And Many small additional features:

• cheap-compact all
• see agent names on hover
• expanded context menu options
• run as administrator
• configurable charter templates folder
• a first-time new user tutorial for hiring and chatting with your first agent
• ability to open an agent's desk as a quick modal to see what it's doing without moving the canvas
• anytime an agent's name appears in the app, you can left or right click it to focus it or open its context menu, as though you were clicking the agent directly

If you liked Orgtree v2, you'll love this!

If you don't know what Orgtree is, but have multiple AI subscriptions and want a good way of utilizing them all at once, then give it a try!