Tootfinder

I haven’t been playing Helldivers as much lately, but man these in game tips are just so well done, and they play on your players ship randomly but it’s nice how they’re actually good advice delivered in world style
https://youtu.be/pcTWzwBacTw

E-THER: A PCT-Grounded Dataset for Benchmarking Empathic AI
Sharjeel Tahir, Judith Johnson, Jumana Abu-Khalaf, Syed Afaq Ali Shah
https://arxiv.org/abs/2509.02100 https://

E-THER: A PCT-Grounded Dataset for Benchmarking Empathic AI
A prevalent shortfall among current empathic AI systems is their inability to recognize when verbal expressions may not fully reflect underlying emotional states. This is because the existing datasets, used for the training of these systems, focus on surface-level emotion recognition without addressing the complex verbal-visual incongruence (mismatch) patterns useful for empathic understanding. In this paper, we present E-THER, the first Person-Centered Therapy-grounded multimodal dataset with …

Bounded PCTL Model Checking of Large Language Model Outputs
Dennis Gross, Helge Spieker, Arnaud Gotlieb
https://arxiv.org/abs/2509.18836 https://arxiv.org/…

Bounded PCTL Model Checking of Large Language Model Outputs
In this paper, we introduce LLMCHECKER, a model-checking-based verification method to verify the probabilistic computation tree logic (PCTL) properties of an LLM text generation process. We empirically show that only a limited number of tokens are typically chosen during text generation, which are not always the same. This insight drives the creation of $α$-$k$-bounded text generation, narrowing the focus to the $α$ maximal cumulative probability on the top-$k$ tokens at every step of the tex…

The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models
Konrad L\"ohr, Shuzhou Yuan, Michael F\"arber
https://arxiv.org/abs/2510.08236

The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models
Large Language Models (LLMs) are increas- ingly integral to information dissemination and decision-making processes. Given their grow- ing societal influence, understanding potential biases, particularly within the political domain, is crucial to prevent undue influence on public opinion and democratic processes. This work investigates political bias and stereotype propa- gation across eight prominent LLMs using the two-dimensional Political Compass Test (PCT). Initially, the PCT is employed to…

Maye's 91 completion pct. tops Brady's Pats mark https://www.espn.com/nfl/story/_/id/46652629/qb-drake-maye-breaks-tom-brady-patriots-record-completion-percentage-win-vs-titans

Coupled tensor models for probability mass function estimation: Part II, Uniqueness of the model
Philippe Flores (CNRS, UGA, Grenoble INP, GIPSA-lab), Konstantin Usevich (CRAN, CNRS, UL), David Brie (CRAN, CNRS, UL)
https://arxiv.org/abs/2509.04931

Coupled tensor models for probability mass function estimation: Part II, Uniqueness of the model
In this paper, uniqueness properties of a coupled tensor model are studied. This new coupled tensor model is used in a new method called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D. This method performs estimation of probability mass functions by coupling 3D marginals, seen as order-3 tensors. The core novelty of PCTF3D's approach (detailed in the part I article) relies on the partial coupling which consists on the choice of 3D marginals to be coupled. Tensor methods are ubiq…

Real-Time Super-Resolution Imaging System Based on Zero-Shot Learning for Infrared Non-Destructive Testing
Pengfei Zhu, Ziang Wei, Ahmad Osman, Clemente Ibarra-Castanedo, Andreas Mandelis, Xavier Maldague, Hai Zhang
https://arxiv.org/abs/2509.10902

Real-Time Super-Resolution Imaging System Based on Zero-Shot Learning for Infrared Non-Destructive Testing
Infrared thermography (IRT) and photothermal coherence tomography (PCT) exhibit potential in non-destructive testing and biomedical fields. However, the inevitable heat diffusion significantly affects the sensitivity and resolution of IRT and PCT. Conventional image processing techniques rely on capturing complete thermal sequences, which limits their ability to achieve real-time processes. Here, we construct a real-time super-resolution imaging system based on zero-shot learning strategy for t…

Coupled tensor models for probability mass function estimation: Part I, Principles and algorithms
Philippe Flores (CNRS, UGA, Grenoble INP, GIPSA-lab), Konstantin Usevich (CRAN, CNRS, UL), David Brie (CRAN, CNRS, UL)
https://arxiv.org/abs/2509.04930

Coupled tensor models for probability mass function estimation: Part I, Principles and algorithms
In this article, a Probability Mass Function (PMF) estimation method which tames the curse of dimensionality is proposed. This method, called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D, has for principle to partially couple order-3 data projections -- seen as order-3 tensors -- to obtain a tensor decomposition of the probability mass tensor. The novelty of PCTF3D relies on partial coupling which consists in choosing a subset of 3D marginals. The choice of marginals is then f…

Replaced article(s) found for cs.MS. https://arxiv.org/list/cs.MS/new
[1/1]:
- FEniCSx-pctools: Tools for PETSc block linear algebra preconditioning in FEniCSx
Martin \v{R}eho\v{r}, Jack S. Hale

Verifying Memoryless Sequential Decision-making of Large Language Models
Dennis Gross, Helge Spieker, Arnaud Gotlieb
https://arxiv.org/abs/2510.06756 https://

Verifying Memoryless Sequential Decision-making of Large Language Models
We introduce a tool for rigorous and automated verification of large language model (LLM)- based policies in memoryless sequential decision-making tasks. Given a Markov decision process (MDP) representing the sequential decision-making task, an LLM policy, and a safety requirement expressed as a PCTL formula, our approach incrementally constructs only the reachable portion of the MDP guided by the LLM's chosen actions. Each state is encoded as a natural language prompt, the LLM's response is pa…