Tootfinder

A Semantics-Aware Hierarchical Self-Supervised Approach to Classification of Remote Sensing Images
Giulio Weikmann, Gianmarco Perantoni, Lorenzo Bruzzone
https://arxiv.org/abs/2510.04916

A Semantics-Aware Hierarchical Self-Supervised Approach to Classification of Remote Sensing Images
Deep learning has become increasingly important in remote sensing image classification due to its ability to extract semantic information from complex data. Classification tasks often include predefined label hierarchies that represent the semantic relationships among classes. However, these hierarchies are frequently overlooked, and most approaches focus only on fine-grained classification schemes. In this paper, we present a novel Semantics-Aware Hierarchical Consensus (SAHC) method for learn…

MachineLearningLM: Continued Pretraining Language Models on Millions of Synthetic Tabular Prediction Tasks Scales In-Context ML
Haoyu Dong, Pengkun Zhang, Mingzhe Lu, Yanzhen Shen, Guolin Ke
https://arxiv.org/abs/2509.06806

MachineLearningLM: Continued Pretraining Language Models on Millions of Synthetic Tabular Prediction Tasks Scales In-Context ML
Large language models (LLMs) possess broad world knowledge and strong general-purpose reasoning ability, yet they struggle to learn from many in-context examples on standard machine learning (ML) tasks, that is, to leverage many-shot demonstrations purely via in-context learning (ICL) without gradient descent. We introduce MachineLearningLM, a portable continued-pretraining framework that equips a general-purpose LLM with robust in-context ML capability while preserving its general knowledge an…

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
Lesly Miculicich, Mihir Parmar, Hamid Palangi, Krishnamurthy Dj Dvijotham, Mirko Montanari, Tomas Pfister, Long T. Le
https://arxiv.org/abs/2510.05156

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
The deployment of autonomous AI agents in sensitive domains, such as healthcare, introduces critical risks to safety, security, and privacy. These agents may deviate from user objectives, violate data handling policies, or be compromised by adversarial attacks. Mitigating these dangers necessitates a mechanism to formally guarantee that an agent's actions adhere to predefined safety constraints, a challenge that existing systems do not fully address. We introduce VeriGuard, a novel framework th…

EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model
Zefu Lin, Rongxu Cui, Chen Hanning, Xiangyu Wang, Junjia Xu, Xiaojuan Jin, Chen Wenbo, Hui Zhou, Lue Fan, Wenling Li, Zhaoxiang Zhang
https://arxiv.org/abs/2510.06207

EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model
Recent advances in control robot methods, from end-to-end vision-language-action frameworks to modular systems with predefined primitives, have advanced robots' ability to follow natural language instructions. Nonetheless, many approaches still struggle to scale to diverse environments, as they often rely on large annotated datasets and offer limited interpretability.In this work, we introduce EmbodiedCoder, a training-free framework for open-world mobile robot manipulation that leverages codin…

An interferometric mid-infrared study of the eruptive star binary Z CMa with MATISSE/VLTI. I. Imaging the protoplanetary disks during the 2023 outburst
F. Lykou, J. Varga, F. Cruz-Sa\'enz de Miera, P. \'Abrah\'am, \'A. K\'osp\'al, B. Lopez, T. Henning, S. Wolf, G. Weigelt, F. Millour, M. Hogerheijde, L. Chen, T. Ratzka, W. Danchi, P. Boley, J. -C. Augereau, P. Priolet

An interferometric mid-infrared study of the eruptive star binary Z CMa with MATISSE/VLTI. I. Imaging the protoplanetary disks during the 2023 outburst
The mid-infrared (MIR) emitting regions of the individual protoplanetary disks in the binary system Z CMa are resolved by MATISSE/VLTI. The observations were obtained during a serendipitous large outburst of the HBe star that lasted more than 100 days, while the FUor companion is presumed to be in quiescence. The size of the MIR-emitting disk region of the more massive HBe star increases toward longer wavelengths from $<14$ mas at 3.5$μm$ to $\ll 50$ mas at 11.5$μm$ . The lack of substructure…

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
Arkadeep Acharya, Akash Ghosh, Pradeepika Verma, Kitsuchart Pasupa, Sriparna Saha, Priti Singh
https://arxiv.org/abs/2510.06888

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
With the increasing use of RetrievalAugmented Generation (RAG), strong retrieval models have become more important than ever. In healthcare, multimodal retrieval models that combine information from both text and images offer major advantages for many downstream tasks such as question answering, cross-modal retrieval, and multimodal summarization, since medical data often includes both formats. However, there is currently no standard benchmark to evaluate how well these models perform in medica…

Rheinmetall baut bald auch Weltraumsatelliten
Der Rüstungskonzern Rheinmetall erweitert sein Portfolio um Weltraum-Satelliten. Dafür wurde ein Gemeinschaftsunternehmen mit der Firma Iceye gegründet.
https://www.

Understanding JWST water spectra: what can thermochemical models tell us about the (cold) water in protoplanetary disks?
Marissa Vlasblom, Milou Temmink, Andrew D. Sellek, Ewine F. van Dishoeck
https://arxiv.org/abs/2509.06494

Understanding JWST water spectra: what can thermochemical models tell us about the (cold) water in protoplanetary disks?
(Abridged) Rotational H$_2$O spectra as observed with JWST/MIRI provide a good probe of the temperature and column density structure of the inner disk. H$_2$O emission can also be influenced by dynamical processes, such as dust grains drifting inwards and their icy mantles sublimating once they cross the snowlines, thus enriching the inner regions in H$_2$O vapor. Recent work has found that this process may leave an imprint in the H$_2$O spectrum in the form of excess flux in the cold H$_2$O li…

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Rui Guo, Yi Zhang, Yhonatan Kvich, Tianyao Huang, Maokun Li, Yonina C. Eldar
https://arxiv.org/abs/2509.04860

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Electromagnetic (EM) imaging is an important tool for non-invasive sensing with low-cost and portable devices. One emerging application is EM stroke imaging, which enables early diagnosis and continuous monitoring of brain strokes. Quantitative imaging is achieved by solving an inverse scattering problem (ISP) that reconstructs permittivity and conductivity maps from measurements. In general, the reconstruction accuracy is limited by its inherent nonlinearity and ill-posedness. Existing methods…