Tootfinder

Modelling shadows in scattered light observations as signals from companions in protoplanetary discs
Deniz Akansoy, Helen C. Petrou, Giulia Ballabio, Anna B. T. Penzlin
https://arxiv.org/abs/2506.04415

Modelling shadows in scattered light observations as signals from companions in protoplanetary discs
Over the past decade, SPHERE scattered light observations of protoplanetary discs have revealed previously unseen features with unprecedented resolution. One such feature are radial streaks of reduced brightness that are commonly interpreted as shadows. A possible cause for these shadows is an embedded companion within the disc. In this work, we use 3D radiative transfer simulations with RADMC-3D to investigate the shadowing effects of embedded companions across a range of orbital distances (5-…

Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search
He Wang, Liang Zeng
https://arxiv.org/abs/2508.03661

Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search
Computational scientific discovery increasingly relies on algorithms to process complex data and identify meaningful patterns - yet faces persistent challenges in gravitational-wave signal identification. While existing algorithmic approaches like matched filtering (MF) and deep neural networks (DNNs) have achieved partial success, their limitations directly stem from fundamental limitations: MF's excessive computational demands arise from its reliance on predefined theoretical waveform templat…

Position Auctions in AI-Generated Content
Santiago Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Di Wang, Song Zuo
https://arxiv.org/abs/2506.03309

Position Auctions in AI-Generated Content
We consider an extension to the classic position auctions in which sponsored creatives can be added within AI generated content rather than shown in predefined slots. New challenges arise from the natural requirement that sponsored creatives should smoothly fit into the context. With the help of advanced LLM technologies, it becomes viable to accurately estimate the benefits of adding each individual sponsored creatives into each potential positions within the AI generated content by properly t…

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker
Qi Li, Shaheer U. Saeed, Yuliang Huang, Mingyuan Luo, Zhongnuo Yan, Jiongquan Chen, Xin Yang, Dong Ni, Nektarios Winter, Phuc Nguyen, Lucas Steinberger, Caelan Haney, Yuan Zhao, Mingjie Jiang, Bowen Ren, SiYeoul Lee, Seonho Kim, MinKyung Seo, MinWoo Kim, Yimeng Dou, Zhiwei Zhang, Yin Li, Tomy Varghese, Dean C. Barratt, Matthew J. Clarkson, Tom Vercauteren, Yipeng Hu

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker
Trackerless freehand ultrasound reconstruction aims to reconstruct 3D volumes from sequences of 2D ultrasound images without relying on external tracking systems, offering a low-cost, portable, and widely deployable alternative for volumetric imaging. However, it presents significant challenges, including accurate inter-frame motion estimation, minimisation of drift accumulation over long sequences, and generalisability across scanning protocols. The TUS-REC2024 Challenge was established to ben…

SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
Ji Qi, Xinchang Zhang, Dingqi Ye, Yongjia Ruan, Xin Guo, Shaowen Wang, Haifeng Li
https://arxiv.org/abs/2506.20599

SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
The rapid advancement of generative artificial intelligence is producing fake remote sensing imagery (RSI) that is increasingly difficult to detect, potentially leading to erroneous intelligence, fake news, and even conspiracy theories. Existing forgery detection methods typically rely on single visual features to capture predefined artifacts, such as spatial-domain cues to detect forged objects like roads or buildings in RSI, or frequency-domain features to identify artifacts from up-sampling …

"Just a strange pic": Evaluating 'safety' in GenAI Image safety annotation tasks from diverse annotators' perspectives
Ding Wang, Mark D\'iaz, Charvi Rastogi, Aida Davani, Vinodkumar Prabhakaran, Pushkar Mishra, Roma Patel, Alicia Parrish, Zoe Ashwood, Michela Paganini, Tian Huey Teh, Verena Rieser, Lora Aroyo
https://

"Just a strange pic": Evaluating 'safety' in GenAI Image safety annotation tasks from diverse annotators' perspectives
Understanding what constitutes safety in AI-generated content is complex. While developers often rely on predefined taxonomies, real-world safety judgments also involve personal, social, and cultural perceptions of harm. This paper examines how annotators evaluate the safety of AI-generated images, focusing on the qualitative reasoning behind their judgments. Analyzing 5,372 open-ended comments, we find that annotators consistently invoke moral, emotional, and contextual reasoning that extends …

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
Mohammed Baharoon, Luyang Luo, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Mahmoud Hussain Alabbad, Maha Sbayel Alhazmi, Neel P. Mistry, Kent Ryan Kleinschmidt, Brady Chrisler, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Noah Michael Prudlo, Mark David Marino, Jeremy Palacio, Rithvik Akula, Hong-Yu Zhou, Ibrahim Ethem Hamamci, Scott J. Adams, Hassan Rayhan AlOmaish, P…

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
We present ReXGroundingCT, the first publicly available dataset to link free-text radiology findings with pixel-level segmentations in 3D chest CT scans that is manually annotated. While prior datasets have relied on structured labels or predefined categories, ReXGroundingCT captures the full expressiveness of clinical language represented in free text and grounds it to spatially localized 3D segmentation annotations in volumetric imaging. This addresses a critical gap in medical AI: the abilit…

Probing Solar Polar Regions
Yuanyong Deng, Hui Tian, Jie Jiang, Shuhong Yang, Hao Li, Robert Cameron, Laurent Gizon, Louise Harra, Robert F. Wimmer-Schweingruber, Fr\'ed\'eric Auch\`ere, Xianyong Bai, Luis Bellot Rubio, Linjie Chen, Pengfei Chen, Lakshmi Pradeep Chitta, Jackie Davies, Fabio Favata, Li Feng, Xueshang Feng, Weiqun Gan, Don Hassler, Jiansen He, Junfeng Hou, Zhenyong Hou, Chunlan Jin, Wenya Li, Jiaben Lin, Dibyendu Nandy, Vaibhav Pant, Marco Romoli, Taro Sakao, Kri…

Probing Solar Polar Regions
The magnetic fields and dynamical processes in the solar polar regions play a crucial role in the solar magnetic cycle and in supplying mass and energy to the fast solar wind, ultimately being vital in controlling solar activities and driving space weather. Despite numerous efforts to explore these regions, to date no imaging observations of the Sun's poles have been achieved from vantage points out of the ecliptic plane, leaving their behavior and evolution poorly understood. This observation …

The Hybrid Renewable Energy Forecasting and Trading Competition 2024
Jethro Browell, Dennis van der Meer, Henrik K\"alvegren, Sebastian Haglund, Edoardo Simioni, Ricardo J. Bessa, Yi Wang
https://arxiv.org/abs/2507.01579

The Hybrid Renewable Energy Forecasting and Trading Competition 2024
The Hybrid Energy Forecasting and Trading Competition challenged participants to forecast and trade the electricity generation from a 3.6GW portfolio of wind and solar farms in Great Britain for three months in 2024. The competition mimicked operational practice with participants required to submit genuine forecasts and market bids for the day-ahead on a daily basis. Prizes were awarded for forecasting performance measured by Pinball Score, trading performance measured by total revenue, and com…

Yop,
Je viens de réuploader ma présentation éclair effectuée Š Pass the Salt 2025, Š propos du déploiement de secrets dans les infrastructures virtualisées en utilisant AF_VSOCK. J'ai ajouté des sous-titres en anglais et en français pour celleux que ça intéresse !
https://peertube.stream/w/eidYHtjaeE6n