Tootfinder

Bringing Everyone to the Table: An Experimental Study of LLM-Facilitated Group Decision Making
Mohammed Alsobay, David M. Rothschild, Jake M. Hofman, Daniel G. Goldstein
https://arxiv.org/abs/2508.08242

Bringing Everyone to the Table: An Experimental Study of LLM-Facilitated Group Decision Making
Group decision-making often suffers from uneven information sharing, hindering decision quality. While large language models (LLMs) have been widely studied as aids for individuals, their potential to support groups of users, potentially as facilitators, is relatively underexplored. We present a pre-registered randomized experiment with 1,475 participants assigned to 281 five-person groups completing a hidden profile task--selecting an optimal city for a hypothetical sporting event--under one o…

UOPSL: Unpaired OCT Predilection Sites Learning for Fundus Image Diagnosis Augmentation
Zhihao Zhao, Yinzheng Zhao, Junjie Yang, Xiangtong Yao, Quanmin Liang, Daniel Zapp, Kai Huang, Nassir Navab, M. Ali Nasseri
https://arxiv.org/abs/2509.08624

UOPSL: Unpaired OCT Predilection Sites Learning for Fundus Image Diagnosis Augmentation
Significant advancements in AI-driven multimodal medical image diagnosis have led to substantial improvements in ophthalmic disease identification in recent years. However, acquiring paired multimodal ophthalmic images remains prohibitively expensive. While fundus photography is simple and cost-effective, the limited availability of OCT data and inherent modality imbalance hinder further progress. Conventional approaches that rely solely on fundus or textual features often fail to capture fine-…

FRaN-X: FRaming and Narratives-eXplorer
Artur Muratov, Hana Fatima Shaikh, Vanshikaa Jani, Tarek Mahmoud, Zhuohan Xie, Daniil Orel, Aaryamonvikram Singh, Yuxia Wang, Aadi Joshi, Hasan Iqbal, Ming Shan Hee, Dhruv Sahnan, Nikolaos Nikolaidis, Purifica\c{c}\~ao Silvano, Dimitar Dimitrov, Roman Yangarber, Ricardo Campos, Al\'ipio Jorge, Nuno Guimar\~aes, Elisa Sartori, Nicolas Stefanovitch, Giovanni Da San Martino, Jakub Piskorski, Preslav Nakov

FRaN-X: FRaming and Narratives-eXplorer
We present FRaN-X, a Framing and Narratives Explorer that automatically detects entity mentions and classifies their narrative roles directly from raw text. FRaN-X comprises a two-stage system that combines sequence labeling with fine-grained role classification to reveal how entities are portrayed as protagonists, antagonists, or innocents, using a unique taxonomy of 22 fine-grained roles nested under these three main categories. The system supports five languages (Bulgarian, English, Hindi, R…

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method
Daniel Scholz, Ayhan Can Erdur, Robbie Holland, Viktoria Ehm, Jan C. Peeken, Benedikt Wiestler, Daniel Rueckert
https://arxiv.org/abs/2509.06592

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method
Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image contrast, hindering data comparability and reproducibility across datasets and clinical studies. Existing scanner harmonization methods, designed to address this challenge, face limitations, such as requiring traveling subjects or struggling to generalize to unseen domains. We propose a novel approach using a conditi…

AT2019cmw: A highly luminous, cooling featureless TDE candidate from the disruption of a high mass star in an early-type galaxy
Jacob Wise, Daniel Perley, Nikhil Sarin, Tatsuya Matsumoto, K-Ryan Hinds, Yuhan Yao, Jesper Sollerman, Steve Schulze, Aleksandra Bochenek, Michael W. Coughlin, Kishalay De, Richard Dekany, Sara Frederick, Christoffer Fremling, Suvi Gezari, Matthew J. Graham, Anna Y. Q. Ho, Shrinivas Kulkarni, Russ R. Laher, Conor Omand, Natalya Pletskova, Yashvi Sharma, Kirsty…

AT2019cmw: A highly luminous, cooling featureless TDE candidate from the disruption of a high mass star in an early-type galaxy
We present optical/UV photometric and spectroscopic observations, as well as X-ray and radio follow-up, of the extraordinary event AT2019cmw. With a peak bolometric luminosity of ~$\mathrm{10^{45.6}\,erg\,s^{-1}}$, it is one of the most luminous thermal transients ever discovered. Extensive spectroscopic follow-up post-peak showed only a featureless continuum throughout its evolution. This, combined with its nuclear location, blue colour at peak and lack of prior evidence of an AGN in its host …

A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain
Simon Pfreundschuh, Malarvizhi Arulraj, Ali Behrangi, Linda Bogerd, Alan James Peixoto Calheiros, Daniele Casella, Neda Dolatabadi, Clement Guilloteau, Jie Gong, Christian D. Kummerow, Pierre Kirstetter, Gyuwon Lee, Maximilian Maahn, Lisa Milani, Giulia Panegrossi, Rayana Palharini, Veljko Petkovi\'c, Soorok Ryu, Paolo San\`o, Jackson Tan

A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain
Accurately tracking the global distribution and evolution of precipitation is essential for both research and operational meteorology. Satellite observations remain the only means of achieving consistent, global-scale precipitation monitoring. While machine learning has long been applied to satellite-based precipitation retrieval, the absence of a standardized benchmark dataset has hindered fair comparisons between methods and limited progress in algorithm development. To address this gap, th…

Achieving quantum-limited sub-Rayleigh identification of incoherent sources with arbitrary intensities
Danilo Triggiani, Cosmo Lupo
https://arxiv.org/abs/2509.03511 https://

Achieving quantum-limited sub-Rayleigh identification of incoherent sources with arbitrary intensities
The Rayleigh diffraction limit imposes a fundamental restriction on the resolution of direct imaging systems, hindering the identification of incoherent optical sources, such as celestial bodies in astronomy and fluorophores in bioimaging. Recent advances in quantum sensing have shown that this limit can be circumvented through spatial demultiplexing (SPADE) and photon detection. Notably, the latter is a semi-classical detection strategy, being SPADE a linear transformation of the field and pho…

From Diagnosis to Therapy: Progress in SPECT and PET Reconstruction for Theranostics
Kweku Enninful, Fardeen Ahmed, Bradley Girod, Richard Laforest, Daniel L. J. Thorek, Vikas Prasad, Abhinav K. Jha
https://arxiv.org/abs/2509.07313

From Diagnosis to Therapy: Progress in SPECT and PET Reconstruction for Theranostics
The theranostic paradigm enables personalization of treatment by selecting patients with a diagnostic radiopharmaceutical and monitoring therapy using a matched therapeutic isotope. This strategy relies on accurate image reconstruction of both pre-therapy and post-therapy images for patient selection and monitoring treatment. However, traditional reconstruction methods are hindered by challenges such as crosstalk in multi-isotope imaging and extremely low-count measurements when imaging of alph…

Guten Morgen,
ich bin schon wieder wach, es ist mir in der zweitkürzesten Nacht des Jahres schon wieder zu hell und warm in der Früh.
Heute gehts nach Hindelang - Alpenrosenköpfle - Zum oberen Horn - Blörchachalpe - Vorderhindelang.
27 Grad sind angesagt und oben ist es hoffentlich kühler. Danach abfrischen in der Prinze Gumpe, leider mit "Textil", das ich noch einpacken muß. Morgen dann ein Badetag am Rottachspeicher :-)
Ihr braucht mir nicht beim Faule…

Interpretable Scalar-on-Image Linear Regression Models via the Generalized Dantzig Selector
Sijia Liao, Xiaoxiao Sun, Ning Hao, Hao Helen Zhang
https://arxiv.org/abs/2508.20278 …

Interpretable Scalar-on-Image Linear Regression Models via the Generalized Dantzig Selector
The scalar-on-image regression model examines the association between a scalar response and a bivariate function (e.g., images) through the estimation of a bivariate coefficient function. Existing approaches often impose smoothness constraints to control the bias-variance trade-off, and thus prevent overfitting. However, such assumptions can hinder interpretability, especially when only certain regions of an image influence changes in the response. In such a scenario, interpretability can be be…