Origin of Hallucination in LLMs, The physical source of hallucinations has found
https://arxiv.org/abs/2512.01797
#HackerNews #OriginOfHallucination #LLMs #AIResearch #MachineLearning #NeuralNetworks #arxiv
Origin of Hallucination in LLMs, The physical source of hallucinations has found
https://arxiv.org/abs/2512.01797
#HackerNews #OriginOfHallucination #LLMs #AIResearch #MachineLearning #NeuralNetworks #arxiv
"Cornell Tech has received more than $7 million from Schmidt Sciences and NASA to upgrade arXiv, an open-access research repository of more than 2.8 million articles. "
It's great news for arXiv. I'm just wondering why they want actually move to the cloud:
"finish migrating to cloud infrastructure"
NREN are providing access for educational networks, I hope the cloud mentioned there is operated by a NREN operator.
🔗 https://news.cornell.edu/stories/2025/11/7m-grant-nasa-schmidt-sciences-upgrade-arxiv
"Cornell Tech has received more than $7 million from Schmidt Sciences and NASA to upgrade arXiv, an open-access research repository of more than 2.8 million articles. "
It's great news for arXiv. I'm just wondering why they want actually move to the cloud:
"finish migrating to cloud infrastructure"
NREN are providing access for educational networks, I hope the cloud mentioned there is operated by a NREN operator.
🔗 https://news.cornell.edu/stories/2025/11/7m-grant-nasa-schmidt-sciences-upgrade-arxiv
"Databricks co-founder argues US must go #OpenSource to beat China in AI."
https://techcrunch.com/2025/11/14/databricks-co-founder-argues-us-must-go-open-source-to-beat-china-in-ai/
"Major #AI labs, including OpenAI, Meta, and Anthropic, continue to innovate significantly, yet their innovations remain largely proprietary… #Konwinski argued that for ideas to truly flourish, they need to be freely exchanged and discussed with the larger academic community. He pointed out that generative AI emerged as a direct result of the #Transformer architecture, a pivotal training technique introduced in a freely available research paper [ #OpenAccess in #arXiv]."
#arXiv will no longer accept #CcomputerScience review papers unless they’re already accepted elsewhere. The reason: too many low-quality and #AI-generated submissions.
#arXiv will no longer accept #CcomputerScience review papers unless they’re already accepted elsewhere. The reason: too many low-quality and #AI-generated submissions.
The Principles of Diffusion Models
https://arxiv.org/abs/2510.21890
#HackerNews #DiffusionModels #Principles #AI #Research #MachineLearning #Arxiv
Given the drama surrounding the arXiv for its dependence on Google and its recent ban on review articles in computer science, I have a question:
Do we still need the arXiv?
Wouldn't a federated network of institutional repositories be a much better option?
Update. In response to this problem (previous post, this thread), some publishers are desk-rejecting papers based on open health datasets. The problem is not the quality of the data, but the absence of additional work to validate findings.
Two reports:
1. "Journals and publishers crack down on research from open health data sets," Science, Oct 8, 2025.
https://www.science.org/content/article/journals-and-publishers-crack-down-research-open-health-data-sets
2. "AI: Journals are automatically rejecting public health dataset papers to combat paper mills," BMJ, Oct 15, 2025.
https://www.bmj.com/content/391/bmj.r2170
( #paywalled)
Update. Here's how #arXiv is dealing with a similar problem in computer science.
https://blog.arxiv.org/2025/10/31/attention-authors-updated-practice-for-review-articles-and-position-papers-in-arxiv-cs-category/
"Before being considered for submission to arXiv’s #CS category, review articles and position papers must now be accepted at a journal or a conference and complete successful peer review…In the past few years, arXiv has been flooded with papers. Generative #AI / #LLMs have added to this flood by making papers – especially papers not introducing new research results – fast and easy to write. While categories across arXiv have all seen a major increase in submissions, it’s particularly pronounced in arXiv’s CS category."
#AISlop killing open submission -
"arXiv’s computer science (CS) category has updated its moderation practice with respect to review (or survey) articles and position papers. Before being considered for submission to arXiv’s CS category, review articles and position papers must now be accepted at a journal or a conference and complete successful peer review."
#AISlop killing open submission -
"arXiv’s computer science (CS) category has updated its moderation practice with respect to review (or survey) articles and position papers. Before being considered for submission to arXiv’s CS category, review articles and position papers must now be accepted at a journal or a conference and complete successful peer review."
Given the drama surrounding the arXiv for its dependence on Google and its recent ban on review articles in computer science, I have a question:
Do we still need the arXiv?
Wouldn't a federated network of institutional repositories be a much better option?
Why is the #arXiv CS category making this change?
“In the past few years, arXiv has been flooded with papers. Generative AI / large language models have added to this flood by making papers – especially papers not introducing new research results – fast and easy to write.”
arXiv No Longer Accepts Computer Science Position or Review Papers Due to LLMs
#HackerNews #arXiv #LLMs #ComputerScience #ResearchUpdates #AcademicPublishing
Beyond Smoothed Analysis: Analyzing the Simplex Method by the Book
https://arxiv.org/abs/2510.21613
#HackerNews #BeyondSmoothedAnalysis #SimplexMethod #AlgorithmResearch #Arxiv #Mathematics
New paper on #ArXiv!
When (coherent) light propagates in a multimode fibre, each mode accumulates a slightly different phase, so the output looks like a random speckle patter.
But it is NOT random!
This non-randomness has a number of consequences, among them the fact that the you get predictable patterns in the apparently random output. We show that a focused input will always result in a ring of excess intensity at the same radius of the input (and suggest how this might be useful).
New paper on #ArXiv!
When (coherent) light propagates in a multimode fibre, each mode accumulates a slightly different phase, so the output looks like a random speckle patter.
But it is NOT random!
This non-randomness has a number of consequences, among them the fact that the you get predictable patterns in the apparently random output. We show that a focused input will always result in a ring of excess intensity at the same radius of the input (and suggest how this might be useful).
Researchers Made a Social Media Platform Where Every User Was AI. The Bots Ended Up at War
#technology #tech #ai #artificialintelligence #socialmedia#arXiv