In the Wikipedia glossary, an orphan is defined as "an article with no links from other pages in the main article namespace". These pages can still be found by searching Wikipedia, but it is preferable that they can also be reachable by links from related pages; it is therefore helpful to add links from other suitable pages with similar or related information. De-orphaning articles is an important aspect of building the web.
Wikipedia, the free encyclopedia
Wikipedia is a free online encyclopedia, created and edited by volunteers around the world and hosted by the Wikimedia Foundation.
Wikipedia, the free encyclopedia
Wikipedia is a free online encyclopedia, created and edited by volunteers around the world and hosted by the Wikimedia Foundation.
The Sites of The Useless Web
The current roster of useless websites on The Useless Web — with the story behind each one.
Wikipedia Editors Adopt ‘Speedy Deletion’ Policy for AI Slop Articles
“The ability to quickly generate a lot of bogus content is problematic if we don't have a way to delete it just as quickly.”
Wikipedia - Lemmy.World
A place to share interesting articles from Wikipedia. Rules: - Only links to Wikipedia permitted (an exception is made for news about Wikipedia, where outside news sources are permitted) - Please stick to the format “Article Title (other descriptive text/editorialization)” - Tick the NSFW box for submissions with inappropriate thumbnails - On Casual Tuesdays, we allow submissions from wikis other than Wikipedia. Recommended: - Use the search box to see if someone has previously submitted an article. Some apps will also notify you if you are resubmitting an article previously shared on Lemmy.
Solutions for Link Rot on the Modern Web
Web links are fundamental to the web, enabling navigation between pages and citations in research articles. However, web links suffer from "link rot", a phenomenon in which links are likely to become inaccessible over time. This can occur if a link’s site disappears, making it impossible to resolve the hostname or establish a server connection, or the linked page has been deleted, resulting in an HTTP 404 "Not Found" error. Today, a common solution to tackle link rot is to rely on web archives, which capture snapshots of web pages for future reference. However, the modern web has evolved significantly since web archives were first introduced, leading to several limitations in their effectiveness. First, the scale of the web has grown tremendously, making it infeasible to crawl every page whenever it changes. As a result, many broken links either have no archived copies, or the archived copies have stale content. Second, modern web pages rely heavily on increasingly complex and diverse JavaScript. This shift has made it more challenging for preserving fidelity in archived copies, significantly increasing both the computational cost of operating browser-based crawlers and engineering effort required to maintain accurate replay systems. This thesis presents a set of solutions to cope with link rot on the modern web. My work aims to mitigate the various limitations of web archives. First, for broken links without any archived copy, or if the archived copy includes stale content or unavailable functionalities, I built Fable. Fable revives the dead link with the new URL to the same page whenever available. Compared to prior approaches, Fable revives 4.6K broken links—a 50% increase—with much higher accuracy. Second, for pages that require dynamic crawling, I show how web archives can achieve a better tradeoff between efficiency and fidelity. By carefully choosing 8.9% of pages to crawl dynamically and strategically reusing resources from those crawls, an archive can serve 99% of the remaining statically crawled pages without any fidelity loss. Third, for fidelity violations in archived copies that are caused by incorrect edits to crawled scripts, I built FidEx. FidEx reliably detects when an archived page differs from its original version and pinpoints the root cause. After fixing the most common errors pinpointed by FidEx, I reduced the fraction of pages for which FidEx reports a violation of fidelity from 15% to 9%.
Solutions for Link Rot on the Modern Web
Web links are fundamental to the web, enabling navigation between pages and citations in research articles. However, web links suffer from "link rot", a phenomenon in which links are likely to become inaccessible over time. This can occur if a link’s site disappears, making it impossible to resolve the hostname or establish a server connection, or the linked page has been deleted, resulting in an HTTP 404 "Not Found" error. Today, a common solution to tackle link rot is to rely on web archives, which capture snapshots of web pages for future reference. However, the modern web has evolved significantly since web archives were first introduced, leading to several limitations in their effectiveness. First, the scale of the web has grown tremendously, making it infeasible to crawl every page whenever it changes. As a result, many broken links either have no archived copies, or the archived copies have stale content. Second, modern web pages rely heavily on increasingly complex and diverse JavaScript. This shift has made it more challenging for preserving fidelity in archived copies, significantly increasing both the computational cost of operating browser-based crawlers and engineering effort required to maintain accurate replay systems. This thesis presents a set of solutions to cope with link rot on the modern web. My work aims to mitigate the various limitations of web archives. First, for broken links without any archived copy, or if the archived copy includes stale content or unavailable functionalities, I built Fable. Fable revives the dead link with the new URL to the same page whenever available. Compared to prior approaches, Fable revives 4.6K broken links—a 50% increase—with much higher accuracy. Second, for pages that require dynamic crawling, I show how web archives can achieve a better tradeoff between efficiency and fidelity. By carefully choosing 8.9% of pages to crawl dynamically and strategically reusing resources from those crawls, an archive can serve 99% of the remaining statically crawled pages without any fidelity loss. Third, for fidelity violations in archived copies that are caused by incorrect edits to crawled scripts, I built FidEx. FidEx reliably detects when an archived page differs from its original version and pinpoints the root cause. After fixing the most common errors pinpointed by FidEx, I reduced the fraction of pages for which FidEx reports a violation of fidelity from 15% to 9%.
What the ephemerality of the Web means for your hyperlinks
Hyperlinks are a powerful tool for journalists and their readers. Diving deep into the context of an article is just a click away. But hyperlinks are a double-edged sword; for all of the internet’s boundlessness, what’s found on the Web can also be modified, moved, or entirely vanished. The fragility of the Web poses an […]
On Link Rot
The web suffers from link rot: hyperlinks that were valid upon creation will often point into nothingness after some time has passed. Within the framework of the web, the typical solution is to link to a snapshot of the original page, hosted on archive.org.
Wikipedia:WikiProject AI Cleanup
Welcome to WikiProject AI Cleanup, a collaboration to combat the increasing problem of poorly written AI-generated content on Wikipedia. If you would like to help, add yourself as a participant in the project, inquire on the talk page, and see the to-do list.
homepages.news — News Homepages documentation
An open-source archive that gathers, saves, shares and analyzes news homepages
Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki
LLM agents require retrieval to behave less like one-shot context fetching and more like reasoning: searching, reading, traversing, and deciding when evidence is sufficient. Yet current Retrieval-Augmented Generation (RAG) systems organize external knowledge as flat chunks retrieved by embedding similarity, exposing a retrieval-as-lookup interface ill-suited to iterative reasoning agents. We propose LLM-Wiki, an agent-native retrieval system that operationalizes the Retrieval-as-Reasoning paradigm by treating external knowledge as a compilable, composable, and self-evolving structure rather than a static retrieval index. LLM-Wiki compiles documents into structured Wiki pages with bidirectional links, exposes search, read, and link-following operations through standard tool-calling interfaces, and introduces an Error Book for persistent structural and semantic self-correction. LLM-Wiki achieves state-of-the-art results on HotpotQA, MuSiQue, and 2WikiMultiHopQA, outperforming HippoRAG 2, LightRAG, and GraphRAG by 2.0-8.1 F1 points. On AuthTrace, LLM-Wiki achieves the best overall accuracy, with especially strong gains on multi-document structured queries, confirming that compilation-based retrieval generalizes beyond chain-style multi-hop reasoning.
Announcing Ibis, the federated Wikipedia Alternative — ibis.wiki
Wikipedia is the most popular online encyclopedia, and millions of people rely on it every day to provide trustworthy information on a wide variety of topics. It is not well known but there have been numerous scandals which put this trust into question. For example in 2012, a trustee of the Wikimedia Foundation UK used his position to place his PR client on Wikipedia's front page 17 times within a month. Wikipedia founder Jimmy Wales made extensive edits to the article about himself, removing mentions of co-founder Larry Sanger. In 2007, a prolific editor who claimed to be a graduate professor and was recruited by Wikipedia staff to the Arbitration Committee was revealed to be a 24-year-old college dropout. These are only a few examples, journalist Helen Buyniski has collected much more information about the the rot in Wikipedia.
Karpathy's LLM Knowledge Base Wiki for Enterprise | Vijoy Pandey posted on the topic | LinkedIn
There's a new kind of computer media in the enterprise: Write once, Read never. The docs are perpetually stale, constantly diverging from reality, and scattered across Confluence, SharePoint, GitHub, Webex (or Slack) threads, Notion, Obsidian - and in my personal life, add Apple Notes, Goodnotes, web clippings, and multiple Google Drives worth of docs and slides that nobody is ever going back to. Karpathy tweeted his LLM knowledge base wiki architecture which went viral last weekend and I decided to give it a run yesterday. Verdict: You *have* to try this out. Prediction: You won’t be able to live without it soon. There were a few mods and decisions I made to the base Karpathy provided. First, the vault / folder structure in Obsidian. I already use Obsidian as a human. Instead of creating separate vaults and dealing with the sync nightmare, I just have folders for Human and Agent, and a Raw folder. (1) The Human/ folder is where I write long form articles and notes independent of the knowledge base wiki. No LLM or agent touches this folder. (2) I do have Arnold Layne, my OpenClaw agent, doing background tasks for me. Raw/ is where both Arnold and I, dump raw snippets. Inclusive of diverse kinds of media. (3) The Agent/ folder is where the LLM (Claude in my case) synthesizes the wiki. No human touches this folder. Second, some customizations to CLAUDE.md for enterprise-like usage - (4) Domain extensions - the agent needs to know that quantum computing and agentic AI have different entity types and different provenance thresholds. (5) Primary source protection, when I drop in my own original work, secondary sources can extend it or raise questions against it, but they cannot overwrite it. It sounds like a small thing but its’s not, especially at enterprise scale where provenance actually matters. Karpathy is upfront that what he’s built is working memory for a single agent, and it’s truly remarkable at that. The jump to Shared Context across teams, reconciling conflicting beliefs at org scale, ontologies that don’t collapse under the weight of a hundred contributors - those are much harder problems and what we are exploring with the Internet of Cognition. PS: The screenshot shows my Obsidian vault after just two runs: one with Karpathy’s original tweet and gist file itself (so meta!) and one with our Internet of Cognition paper. Claude (Sonnet) read it, compiled it into structured summaries, entity pages, concept pages, backlinks, merged all the information cohesively, and keeps it all maintained from there. You just read the Wiki. It’s simply magical.
Today is the official launch of lichen.wiki in the @atmosphere.community !! It’s an open source collaborative website built on @atproto.com, the decentralized protocol behind Bluesky You can create wikis, add markdown notes, and link them together with internal links!
Lichen
lichen.wiki