Tootfinder

Non-Normal Eigenvector Amplification in Multi-Dimensional Kesten Processes
Virgile Troude, Didier Sornette
https://arxiv.org/abs/2510.11763 https://arxiv.o…

Non-Normal Eigenvector Amplification in Multi-Dimensional Kesten Processes
Heavy-tailed fluctuations and power law statistics pervade physics, finance, and economics, yet their origin is often ascribed to systems poised near criticality. Here we show that such behavior can emerge far from instability through a universal mechanism of non-normal eigenvector amplification in multidimensional Kesten processes $x_{t+1}=A_t x_t+η_t$, where $A_t$ are random interaction matrices and $η_t$ represents external inputs, capturing the evolving interdependence among $N$ coupled c…

Few Shot Semi-Supervised Learning for Abnormal Stop Detection from Sparse GPS Trajectories
Muhammad Ayub Sabir, Junbiao Pang, Jiaqi Wu, Fatima Ashraf
https://arxiv.org/abs/2510.12686

Few Shot Semi-Supervised Learning for Abnormal Stop Detection from Sparse GPS Trajectories
Abnormal stop detection (ASD) in intercity coach transportation is critical for ensuring passenger safety, operational reliability, and regulatory compliance. However, two key challenges hinder ASD effectiveness: sparse GPS trajectories, which obscure short or unauthorized stops, and limited labeled data, which restricts supervised learning. Existing methods often assume dense sampling or regular movement patterns, limiting their applicability. To address data sparsity, we propose a Sparsity-Aw…

Europe’s populist worries will intensify today
when right-wing billionaire Andrej Babiš becomes Czech prime minister.
Combined with Hungary’s Viktor Orbšn and Slovakia’s Robert Fico,
Babiš has the potential to jam up the legislative machinery in Brussels as it works on key files.
Czech President Petr Pavel is set to appoint Babiš to the position
after resolvinglongstanding conflict-of-interest issues related to the PM-elect’s conglomerate, Agrofert.
Babiš…

New Czech PM Babiš is poised to aggravate Brussels’ populist headache
Andrej Babiš could find common cause with Hungary’s Viktor Orbán and Slovakia’s Robert Fico on several issues.

Efficient Autoregressive Inference for Transformer Probabilistic Models
Conor Hassan, Nasrulloh Loka, Cen-You Li, Daolang Huang, Paul E. Chang, Yang Yang, Francesco Silvestrin, Samuel Kaski, Luigi Acerbi
https://arxiv.org/abs/2510.09477

Efficient Autoregressive Inference for Transformer Probabilistic Models
Transformer-based models for amortized probabilistic inference, such as neural processes, prior-fitted networks, and tabular foundation models, excel at single-pass marginal prediction. However, many real-world applications, from signal interpolation to multi-column tabular predictions, require coherent joint distributions that capture dependencies between predictions. While purely autoregressive architectures efficiently generate such distributions, they sacrifice the flexible set-conditioning…

Trump expects loyalty from those who benefit from him.
Days after issuing him a pardon,
Donald Trump criticized US House member
Henry Cuellar of Texas
for deciding to run for re-election as a Democrat.
Trump pardoned Cuellar and the congressman’s wife on Wednesday as they faced bribery charges.
They were alleged to have accepted thousands of dollars from Azerbaijan and a Mexican bank in exchange for advancing their interests.
Shortly after the pardo…

"Our government is being run by aggrieved elites who were thrown onto social platforms with everyone else in the 2010s, where they could finally read what we all think about them. And it caused them so much psychic damage that they have decided to destroy both the internet and democracy to make sure nothing like it will ever happen again."
(Original title: Petty, powerful, and pathologically online)

Petty, powerful, and pathologically online
Read to the end for an academic paper on puppygirls

Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
Riccardo Mereu, Aidan Scannell, Yuxin Hou, Yi Zhao, Aditya Jitta, Antonio Dominguez, Luigi Acerbi, Amos Storkey, Paul Chang
https://arxiv.org/abs/2510.07092

Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model Challenge introduces an open-source benchmark of real-world humanoid interaction, with two complementary tracks: sampling, focused on forecasting future image frames, and compression, focused on predicting future discrete latent codes. For the sampling track, we adapt the video generation foundation model Wan-2.2 TI2V-…

DeepCodeSeek: Real-Time API Retrieval for Context-Aware Code Generation
Esakkivel Esakkiraja, Denis Akhiyarov, Aditya Shanmugham, Chitra Ganapathy
https://arxiv.org/abs/2509.25716

DeepCodeSeek: Real-Time API Retrieval for Context-Aware Code Generation
Current search techniques are limited to standard RAG query-document applications. In this paper, we propose a novel technique to expand the code and index for predicting the required APIs, directly enabling high-quality, end-to-end code generation for auto-completion and agentic AI applications. We address the problem of API leaks in current code-to-code benchmark datasets by introducing a new dataset built from real-world ServiceNow Script Includes that capture the challenge of unclear API us…

Deep Learning-Based Approach for Improving Relational Aggregated Search
Sara Saad Soliman, Ahmed Younes, Islam Elkabani, Ashraf Elsayed
https://arxiv.org/abs/2510.00966 https://…

Deep Learning-Based Approach for Improving Relational Aggregated Search
Due to an information explosion on the internet, there is a need for the development of aggregated search systems that can boost the retrieval and management of content in various formats. To further improve the clustering of Arabic text data in aggregated search environments, this research investigates the application of advanced natural language processing techniques, namely stacked autoencoders and AraBERT embeddings. By transcending the limitations of traditional search engines, which are i…

Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Nevan Wichers, Aram Ebtekar, Ariana Azarbal, Victor Gillioz, Christine Ye, Emil Ryd, Neil Rathi, Henry Sleight, Alex Mallen, Fabien Roger, Samuel Marks
https://arxiv.org/abs/2510.05024

Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Large language models are sometimes trained with imperfect oversight signals, leading to undesired behaviors such as reward hacking and sycophancy. Improving oversight quality can be expensive or infeasible, motivating methods that improve learned behavior despite an imperfect training signal. We introduce Inoculation Prompting (IP), a simple but counterintuitive technique that prevents learning of an undesired behavior by modifying training prompts to explicitly request it. For example, to ino…