Tootfinder

MetaLint: Generalizable Idiomatic Code Quality Analysis through Instruction-Following and Easy-to-Hard Generalization
Atharva Naik, Lawanya Baghel, Dhakshin Govindarajan, Darsh Agrawal, Daniel Fried, Carolyn Rose
https://arxiv.org/abs/2507.11687

MetaLint: Generalizable Idiomatic Code Quality Analysis through Instruction-Following and Easy-to-Hard Generalization
Large Language Models, though successful in code generation, struggle with code quality analysis because they are limited by static training data and can't easily adapt to evolving best practices. We introduce MetaLint, a new instruction-following framework that formulates code quality analysis as the task of detecting and fixing problematic semantic code fragments or code idioms based on high-level specifications. Unlike conventional approaches that train models on static, rule-based data, Met…

Mgmt: We don't have the resources to make our own LLM. Can we just monetize AI prompts?
Business School Student: Hold my beer 🍺
#blockchain

PromptChain: A Decentralized Web3 Architecture for Managing AI Prompts as Digital Assets
We present PromptChain, a decentralized Web3 architecture that establishes AI prompts as first-class digital assets with verifiable ownership, version control, and monetization capabilities. Current centralized platforms lack mechanisms for proper attribution, quality assurance, or fair compensation for prompt creators. PromptChain addresses these limitations through a novel integration of IPFS for immutable storage, smart contracts for governance, and token incentives for community curation. O…

Holey sheets: Double-Threshold Rupture of Draining Liquid Films
Ayush K. Dixit, Chunheng Zhao, St\'ephane Zaleski, Detlef Lohse, Vatsal Sanjay
https://arxiv.org/abs/2509.12789

Holey sheets: Double-Threshold Rupture of Draining Liquid Films
Classical rupture is attributed to molecular (van der Waals) forces acting at nanometric thicknesses. Nonetheless, micron-thick liquid sheets routinely perforate far above the scale where these molecular forces act, yet the mechanism that selects opening versus healing has remained unclear. Using direct numerical simulations of a draining sheet with an entrained air bubble (cavity), we show that irreversible rupture occurs only when a deterministic double-threshold is crossed: (i) the outward d…

It very much bothers me that #smartd didn't email me about this. The only reason I noticed it is because 'snapraid smart' output says that the chance of the drive failing in the next year is 99%. #SelfHosting

Even if “AI” worked (it doesn’t), there’s many reasons why you shouldn’t use it:
1. It’s destroying Internet sites that you love as you use chat bots instead of actually going to sources of information—this will cause them to be less active and eventually shut down.
2. Pollution and water use from server farms cause immediate harm; often—just like other heavy industry—these are built in underprivileged communities and harming poor people. Without any benefits as the big tech companies get tax breaks and don’t pay for power, while workers aren’t from the community but commute in.
3. The basic underlying models of any LLM rely on stolen data, even when specific extra data is obtained legally. Chatbots can’t learn to speak English just by reading open source code.
4. You’re fueling a speculation bubble that is costing many people their jobs—because the illusion of “efficiency” is kept up by firing people and counting that as profit.
5. Whenever you use the great cheat machine in the cloud you’re robbing yourself from doing real research, writing or coding—literally atrophying your brain and making you stupider.
It’s a grift, through and through.

Dual Knowledge-Enhanced Two-Stage Reasoner for Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Haokun Wen, Weili Guan, Xiangyu Zhao, Liqiang Nie
https://arxiv.org/abs/2509.07817

Dual Knowledge-Enhanced Two-Stage Reasoner for Multimodal Dialog Systems
Textual response generation is pivotal for multimodal \mbox{task-oriented} dialog systems, which aims to generate proper textual responses based on the multimodal context. While existing efforts have demonstrated remarkable progress, there still exist the following limitations: 1) \textit{neglect of unstructured review knowledge} and 2) \textit{underutilization of large language models (LLMs)}. Inspired by this, we aim to fully utilize dual knowledge (\textit{i.e., } structured attribute and un…

𝕮𝖆𝖙𝖚𝖗𝖉𝖆𝖞 𝕾𝖕𝖊𝖈𝖎𝖆𝖑 𝕰𝖉𝖎𝖙𝖎𝖔𝖓: Three adorbs cats in my neighborhood (sounds like I'm posting to NextDoor!)
#cats #photo #photography

Credit reporting giant TransUnion has disclosed a data breach
affecting more than 4.4 million customers’ personal information.
In a filing with Maine’s attorney general’s office on Thursday, TransUnion attributed the July 28 breach to unauthorized access of a third-party application storing customers’ personal data for its U.S. consumer support operations.
TransUnion claimed “no credit information was accessed,” but provided no immediate evidence for its claim.
The d…

TransUnion says hackers stole 4.4 million customers' personal information | TechCrunch
The credit reporting giant confirmed unauthorized access to a third-party application storing the personal information of its customers, including Social Security numbers.

Poster No 857: Plastic changes in the occipital regions during pitch perception associate with blindness onset age; "Specifically, the primary visual cortex remains engaged in pitch processing tasks following late blindness." https://doi.org/10.5281/zenodo.15641972

Classification by Separating Hypersurfaces: An Entropic Approach
Argimiro Arratia, Mahmoud El Daou, Henryk Gzyl
https://arxiv.org/abs/2507.02732 https://…

Classification by Separating Hypersurfaces: An Entropic Approach
We consider the following classification problem: Given a population of individuals characterized by a set of attributes represented as a vector in ${\mathbb R}^N$, the goal is to find a hyperplane in ${\mathbb R}^N$ that separates two sets of points corresponding to two distinct classes. This problem, with a history dating back to the perceptron model, remains central to machine learning. In this paper we propose a novel approach by searching for a vector of parameters in a bounded $N$-dimensi…