Tootfinder

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Weike Zhao, Chaoyi Wu, Yanjie Fan, Xiaoman Zhang, Pengcheng Qiu, Yuze Sun, Xiao Zhou, Yanfeng Wang, Ya Zhang, Yongguo Yu, Kun Sun, Weidi Xie
https://arxiv.org/abs/2506.20430

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Rare diseases collectively affect over 300 million individuals worldwide, yet timely and accurate diagnosis remains a pervasive challenge. This is largely due to their clinical heterogeneity, low individual prevalence, and the limited familiarity most clinicians have with rare conditions. Here, we introduce DeepRare, the first rare disease diagnosis agentic system powered by a large language model (LLM), capable of processing heterogeneous clinical inputs. The system generates ranked diagnostic…

On the space of metrics with non-positive curvature
Yasha Savelyev
https://arxiv.org/abs/2506.19983 https://arxiv.org/pdf/2506.19983

On the space of metrics with non-positive curvature
Let $\mathcal{M} (X)$ denote the space of complete Riemannian metrics with non-positive sectional curvature and with negatively curved ends, on a manifold $X$. We show that $\mathcal{M} (\mathbb{R} \times S ^{1}) $ and $\mathcal{M} (\mathbb{R} ^{} \times Y)$ are path disconnected, where $Y$ is compact and admits a negative curvature metric. The proof is very concise, using as the main ingredient Fuller index theory. Furthermore, we get a new metric deformation invariant based on geodesic string…

SViP: Sequencing Bimanual Visuomotor Policies with Object-Centric Motion Primitives
Yizhou Chen, Hang Xu, Dongjie Yu, Zeqing Zhang, Yi Ren, Jia Pan
https://arxiv.org/abs/2506.18825

SViP: Sequencing Bimanual Visuomotor Policies with Object-Centric Motion Primitives
Imitation learning (IL), particularly when leveraging high-dimensional visual inputs for policy training, has proven intuitive and effective in complex bimanual manipulation tasks. Nonetheless, the generalization capability of visuomotor policies remains limited, especially when small demonstration datasets are available. Accumulated errors in visuomotor policies significantly hinder their ability to complete long-horizon tasks. To address these limitations, we propose SViP, a framework that se…

NeRF-based CBCT Reconstruction needs Normalization and Initialization
Zhuowei Xu, Han Li, Dai Sun, Zhicheng Li, Yujia Li, Qingpeng Kong, Zhiwei Cheng, Nassir Navab, S. Kevin Zhou
https://arxiv.org/abs/2506.19742

NeRF-based CBCT Reconstruction needs Normalization and Initialization
Cone Beam Computed Tomography (CBCT) is widely used in medical imaging. However, the limited number and intensity of X-ray projections make reconstruction an ill-posed problem with severe artifacts. NeRF-based methods have achieved great success in this task. However, they suffer from a local-global training mismatch between their two key components: the hash encoder and the neural network. Specifically, in each training step, only a subset of the hash encoder's parameters is used (local sparse…

An S-shaped filament formed due to Cloud-Cloud Collision in molecular cloud G178.28-00.61
Tianwei Zhang, Tie Liu, Yuefang Wu, Linjing Feng, Sihan Jiao, Derek Ward-Thompson, Alessio Traficante, Helen J Fraser, James Di Francesco, Doug Johnstone, Paul F. Goldsmith, Yasuo Doi, Xunchuan Liu, Chang Won Lee, Fengwei Xu, Ram K. Yadav, Glenn J White, Leonardo Bronfman, Yi-Jehng Kuan, Kee-Tae Kim, Donghui Quan

An S-shaped filament formed due to Cloud-Cloud Collision in molecular cloud G178.28-00.61
We present compelling observational evidence supporting G178.28-00.61 as an early-stage candidate for Cloud-Cloud Collision (CCC), with indications of the formation of an S-shaped filament, evenly-separated dense cores, and young star clusters. The observations of CO molecular line emission demonstrate the existence of two interacting molecular clouds with systemic velocities of 0.8 km/s and -1.2 km/s, respectively. The convergence zone of these two clouds reveals an S-shaped filament in the JC…

Understanding the Supply Chain and Risks of Large Language Model Applications
Yujie Ma, Lili Quan, Xiaofei Xie, Qiang Hu, Jiongchi Yu, Yao Zhang, Sen Chen
https://arxiv.org/abs/2507.18105

Understanding the Supply Chain and Risks of Large Language Model Applications
The rise of Large Language Models (LLMs) has led to the widespread deployment of LLM-based systems across diverse domains. As these systems proliferate, understanding the risks associated with their complex supply chains is increasingly important. LLM-based systems are not standalone as they rely on interconnected supply chains involving pretrained models, third-party libraries, datasets, and infrastructure. Yet, most risk assessments narrowly focus on model or data level, overlooking broader s…

RECALLED: An Unbounded Resource Consumption Attack on Large Vision-Language Models
Haoran Gao, Yuanhe Zhang, Zhenhong Zhou, Lei Jiang, Fanyu Meng, Yujia Xiao, Kun Wang, Yang Liu, Junlan Feng
https://arxiv.org/abs/2507.18053

RECALLED: An Unbounded Resource Consumption Attack on Large Vision-Language Models
Resource Consumption Attacks (RCAs) have emerged as a significant threat to the deployment of Large Language Models (LLMs). With the integration of vision modalities, additional attack vectors exacerbate the risk of RCAs in large vision-language models (LVLMs). However, existing red-teaming studies have largely overlooked visual inputs as a potential attack surface, resulting in insufficient mitigation strategies against RCAs in LVLMs. To address this gap, we propose RECALLED (\textbf{RE}source…

Finite-Time Information-Theoretic Bounds in Queueing Control
Yujie Liu, Vincent Y. F. Tan, Yunbei Xu
https://arxiv.org/abs/2506.18278 https://

Finite-Time Information-Theoretic Bounds in Queueing Control
We establish the first finite-time information-theoretic lower bounds-and derive new policies that achieve them-for the total queue length in scheduling problems over stochastic processing networks with both adversarial and stochastic arrivals. Prior analyses of MaxWeight guarantee only stability and asymptotic optimality in heavy traffic; we prove that, at finite horizons, MaxWeight can incur strictly larger backlog by problem-dependent factors which we identify. Our main innovations are 1) a …

Defect-Mediated Aggregation and Motility-Induced Phase Separation in Active XY Model
Shun Inoue, Satoshi Yukawa
https://arxiv.org/abs/2507.17108 https://ar…

Defect-Mediated Aggregation and Motility-Induced Phase Separation in Active XY Model
We propose an ``active XY model'' that incorporates key elements of both the classical XY model and the Vicsek model to study the role of topological defects in active matter systems. This model features self-propelled particles with XY spin degrees of freedom on a lattice and introduces a self-propulsion parameter controlling the directional bias of particle motion. Using numerical simulations, we demonstrate that self-propulsion induces motility-induced phase separation (MIPS), where particle…

GR-3 Technical Report
Chilam Cheang, Sijin Chen, Zhongren Cui, Yingdong Hu, Liqun Huang, Tao Kong, Hang Li, Yifeng Li, Yuxiao Liu, Xiao Ma, Hao Niu, Wenxuan Ou, Wanli Peng, Zeyu Ren, Haixin Shi, Jiawen Tian, Hongtao Wu, Xin Xiao, Yuyang Xiao, Jiafeng Xu, Yichu Yang
https://arxiv.org/abs/2507.15493

GR-3 Technical Report
We report our recent progress towards building generalist robot policies, the development of GR-3. GR-3 is a large-scale vision-language-action (VLA) model. It showcases exceptional capabilities in generalizing to novel objects, environments, and instructions involving abstract concepts. Furthermore, it can be efficiently fine-tuned with minimal human trajectory data, enabling rapid and cost-effective adaptation to new settings. GR-3 also excels in handling long-horizon and dexterous tasks, inc…