Tootfinder

Mask Consistency Regularization in Object Removal
Hua Yuan, Jin Yuan, Yicheng Jiang, Yao Zhang, Xin Geng, Yong Rui
https://arxiv.org/abs/2509.10259 https://

Mask Consistency Regularization in Object Removal
Object removal, a challenging task within image inpainting, involves seamlessly filling the removed region with content that matches the surrounding context. Despite advancements in diffusion models, current methods still face two critical challenges. The first is mask hallucination, where the model generates irrelevant or spurious content inside the masked region, and the second is mask-shape bias, where the model fills the masked area with an object that mimics the mask's shape rather than su…

Want a used car that works?
You’d be wise to not get an older Tesla.
In Consumer Reports’ latest ranking for used cars,
the Elon Musk-run automaker came dead last in terms of reliability,
trailing by over forty points from the top spot on a scale between 0 and 100
https://futurism.co…

Old Teslas Are Falling Apart
On Consumer Reports' latest ranking of used car reliability, Tesla came in dead last with a rating not even half of the top placed brand.

Anisotropic Strain Engineering in La0.7Sr0.3MnO3/LaFeO3 Superlattice: Structural Relaxation and Domain Formation
Yu Liu, Thea Marie Dale, Emma van der Minne, Susanne Boucher, Romar Avila, Christoph Klewe, Gertjan Koster, Magnus Nord, Mari-Ann Einarsrud, Ingrid Hallsteinsen
https://arxiv.org/abs/2510.10482

Anisotropic Strain Engineering in La0.7Sr0.3MnO3/LaFeO3 Superlattice: Structural Relaxation and Domain Formation
Anisotropic strain engineering in epitaxial oxide films provides new opportunities to control the antiferromagnetic and structural properties crucial for advancements of antiferromagnetic spintronics. Here we report on a (La0.7Sr0.3MnO3/LaFeO3)4 superlattice grown on (101)o DyScO3 substrate which imposes significant anisotropic in-plane strain. Reciprocal space mapping reveals selective strain relaxation along the tensile in-plane [010]o axis, while compression along the perpendicular in-plane …

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Mohammad Tamim Kashifi
https://arxiv.org/abs/2510.09886

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Over the past decade, there has been a growing trend toward integrating human factors (HF) into traffic flow models to better understand the complexities of human behavior and its impact on traffic dynamics. This research seeks to advance this trend by bridging the gap between traditional car-following models and the inherent variability of human driving behavior. By incorporating these elements, our models provide valuable insights into how driver behavior adaptation and risk-taking influence …

I've almost missed my train today while filling bugs over another #slop release of #autobahn. This was the last straw. Well, the penultimate one, though I don't know why I'm even bothering.
#Python #NoAI

DACIP-RC: Domain Adaptive Continual Instruction Pre-Training via Reading Comprehension on Business Conversations
Elena Khasanova, Harsh Saini, Md Tahmid Rahman Laskar, Xue-Yong Fu, Cheng Chen, Shashi Bhushan TN
https://arxiv.org/abs/2510.08152

DACIP-RC: Domain Adaptive Continual Instruction Pre-Training via Reading Comprehension on Business Conversations
The rapid advancements in Large Language Models (LLMs) have enabled their adoption in real-world industrial scenarios for various natural language processing tasks. However, the high inference cost of large-scale LLMs makes their deployment impractical, necessitating the use of smaller models. Despite their efficiency, smaller LLMs lack robust zero-shot instruction-following capabilities across diverse domains, limiting their adaptability to dynamic user requirements. Traditional fine-tuning ap…

The Senate on Thursday night approved its $925 billion version of the
National Defense Authorization Act,
the annual must-pass Pentagon policy blueprint,
setting up what is expected to be a lengthy negotiation with the House to finalize the bill.

The legislation, deadlocked for weeks over various partisan disagreements,
advanced by a margin of 77 to 20 following amendment votes earlier in the evening.

Senate and House staff will next reconcile their bills…

Senate passes $925 billion defense bill, setting up House talks
Staff from both chambers must now negotiate final, compromise legislation ahead of a vote expected later this fall.

InstructX: Towards Unified Visual Editing with MLLM Guidance
Chong Mou, Qichao Sun, Yanze Wu, Pengze Zhang, Xinghui Li, Fulong Ye, Songtao Zhao, Qian He
https://arxiv.org/abs/2510.08485

InstructX: Towards Unified Visual Editing with MLLM Guidance
With recent advances in Multimodal Large Language Models (MLLMs) showing strong visual understanding and reasoning, interest is growing in using them to improve the editing performance of diffusion models. Despite rapid progress, most studies lack an in-depth analysis of MLLM design choices. Moreover, the integration of MLLMs and diffusion models remains an open challenge in some difficult tasks, such as video editing. In this paper, we present InstructX, a unified framework for image and video…

Albany Georgia isn’t the only place where the poorest among us are also the sickest.
The United States is blessed with one of the most scientifically and technologically advanced health care systems in the world,
a sprawling industry so vast and lucrative that it is now one of the largest drivers of the economy,
accounting for more jobs and revenue than manufacturing.
But for all the money flowing in and out,
Americans have more chronic illnesses and shorte…

Sick in a Hospital Town
Welcome to Albany, Georgia, where one hospital dominates the political and economic landscape. The story of Phoebe Putney Memorial is the story of American health care.

SciVideoBench: Benchmarking Scientific Video Reasoning in Large Multimodal Models
Andong Deng, Taojiannan Yang, Shoubin Yu, Lincoln Spencer, Mohit Bansal, Chen Chen, Serena Yeung-Levy, Xiaohan Wang
https://arxiv.org/abs/2510.08559

SciVideoBench: Benchmarking Scientific Video Reasoning in Large Multimodal Models
Large Multimodal Models (LMMs) have achieved remarkable progress across various capabilities; however, complex video reasoning in the scientific domain remains a significant and challenging frontier. Current video benchmarks predominantly target general scenarios where perception/recognition is heavily relied on, while with relatively simple reasoning tasks, leading to saturation and thus failing to effectively evaluate advanced multimodal cognitive skills. To address this critical gap, we intr…