Tootfinder

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level
Sezen Per\c{c}in, Xin Su, Qutub Sha Syed, Phillip Howard, Aleksei Kuvshinov, Leo Schwinn, Kay-Ulrich Scholl
https://arxiv.org/abs/2507.06956

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level
Large language models (LLMs) are very costly and inefficient to update with new information. To address this limitation, retrieval-augmented generation (RAG) has been proposed as a solution that dynamically incorporates external knowledge during inference, improving factual consistency and reducing hallucinations. Despite its promise, RAG systems face practical challenges-most notably, a strong dependence on the quality of the input query for accurate retrieval. In this paper, we investigate th…

Bounding quantum uncommon information with quantum neural estimators
Donghwa Ji, Junseo Lee, Myeongjin Shin, IlKwon Sohn, Kabgyun Jeong
https://arxiv.org/abs/2507.06091

Bounding quantum uncommon information with quantum neural estimators
In classical information theory, uncommon information refers to the amount of information that is not shared between two messages, and it admits an operational interpretation as the minimum communication cost required to exchange the messages. Extending this notion to the quantum setting, quantum uncommon information is defined as the amount of quantum information necessary to exchange two quantum states. While the value of uncommon information can be computed exactly in the classical case, no …

A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
TRI LBM Team, Jose Barreiros, Andrew Beaulieu, Aditya Bhat, Rick Cory, Eric Cousineau, Hongkai Dai, Ching-Hsin Fang, Kunimatsu Hashimoto, Muhammad Zubair Irshad, Masha Itkina, Naveen Kuppuswamy, Kuan-Hui Lee, Katherine Liu, Dale McConachie, Ian McMahon, Haruki Nishimura, Calder Phillips-Grafflin, Charles Richter, Paarth Shah, Krishnan Srinivasan, Blake Wulfe, Chen Xu, Mengchao Zhang, Alex Alspach, Maya …

A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
Robot manipulation has seen tremendous progress in recent years, with imitation learning policies enabling successful performance of dexterous and hard-to-model tasks. Concurrently, scaling data and model size has led to the development of capable language and vision foundation models, motivating large-scale efforts to create general-purpose robot foundation models. While these models have garnered significant enthusiasm and investment, meaningful evaluation of real-world performance remains a …

Replaced article(s) found for physics.geo-ph. https://arxiv.org/list/physics.geo-ph/new
[1/1]:
- Lie Group Theory of Multipole Moments and Shape of Stationary Rotating Fluid Bodies
Sergei M. Kopeikin (University of Missouri-Columbia, USA)

First Contact: Data-driven Friction-Stir Process Control
James Koch, Ethan King, WoongJo Choi, Megan Ebers, David Garcia, Ken Ross, Keerti Kappagantula
https://arxiv.org/abs/2507.03177

First Contact: Data-driven Friction-Stir Process Control
This study validates the use of Neural Lumped Parameter Differential Equations for open-loop setpoint control of the plunge sequence in Friction Stir Processing (FSP). The approach integrates a data-driven framework with classical heat transfer techniques to predict tool temperatures, informing control strategies. By utilizing a trained Neural Lumped Parameter Differential Equation model, we translate theoretical predictions into practical set-point control, facilitating rapid attainment of des…

Study of the peculiar variable star Khavchenko 1
A. E. Maslak, D. V. Denisenko
https://arxiv.org/abs/2507.00149 https://arxiv.org/pdf…

Study of the peculiar variable star Khavchenko 1
The work is devoted to the study of the peculiar variable star Khavchenko 1 in Auriga. It was discovered by the 7th grade student Sergey Khavchenko in 2020. The brightness of the star varies with an amplitude of about 0.4 magnitude and the period of 4.213 days. Initially the star could not have been attributed to any known type of variability. Its light curve looks like the upside-down light curve of the eclipsing binary similar to that of luminous red nova V1309 Scorpii a few years before the …

Cross-Dataset Semantic Segmentation Performance Analysis: Unifying NIST Point Cloud City Datasets for 3D Deep Learning
Alexander Nikitas Dimopoulos, Joseph Grasso
https://arxiv.org/abs/2508.00822

Cross-Dataset Semantic Segmentation Performance Analysis: Unifying NIST Point Cloud City Datasets for 3D Deep Learning
This study analyzes semantic segmentation performance across heterogeneously labeled point-cloud datasets relevant to public safety applications, including pre-incident planning systems derived from lidar scans. Using NIST's Point Cloud City dataset (Enfield and Memphis collections), we investigate challenges in unifying differently labeled 3D data. Our methodology employs a graded schema with the KPConv architecture, evaluating performance through IoU metrics on safety-relevant features. Resul…

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Replaced article(s) found for physics.class-ph. https://arxiv.org/list/physics.class-ph/new
[1/1]:
- Lie Group Theory of Multipole Moments and Shape of Stationary Rotating Fluid Bodies
Sergei M. Kopeikin (University of Missouri-Columbia, USA)