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BreastDCEDL: Curating a Comprehensive DCE-MRI Dataset and developing a Transformer Implementation for Breast Cancer Treatment Response Prediction
Naomi Fridman, Bubby Solway, Tomer Fridman, Itamar Barnea, Anat Goldshtein
https://arxiv.org/abs/2506.12190

BreastDCEDL: Curating a Comprehensive DCE-MRI Dataset and developing a Transformer Implementation for Breast Cancer Treatment Response Prediction
Breast cancer remains a leading cause of cancer-related mortality worldwide, making early detection and accurate treatment response monitoring critical priorities. We present BreastDCEDL, a curated, deep learning-ready dataset comprising pre-treatment 3D Dynamic Contrast-Enhanced MRI (DCE-MRI) scans from 2,070 breast cancer patients drawn from the I-SPY1, I-SPY2, and Duke cohorts, all sourced from The Cancer Imaging Archive. The raw DICOM imaging data were rigorously converted into standardized…

What is and is not inside a Cayley graph?
Kolja Knauer, Alvaro Soto Gomez
https://arxiv.org/abs/2506.14088 https://arxiv.org/pdf/2506…

What is and is not inside a Cayley graph?
In this note we show that there is a cubic graph of girth $5$ that is not a subgraph of any minimal Cayley graph. On the other hand, we show that any Generalized Petersen Graph $G(n,k)$ with $\gcd(n,k)=1$ is an induced subgraph of a minimal Cayley graph. These results give insights into two comments of László Babai in [L. Babai, \emph{Automorphism groups, isomorphism, reconstruction}. Graham, R. L. (ed.) et al., Handbook of combinatorics. Vol. 1-2, 1994].

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https://www.noz.de/lokales/osnabrueck/artikel/osnabrueck-insolvenzverwalter-soll-im-landwehrviertel-aufraeumen-48716002
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Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics
Asifullah khan, Muhammad Zaeem Khan, Saleha Jamshed, Sadia Ahmad, Aleesha Zainab, Kaynat Khatib, Faria Bibi, Abdul Rehman
https://arxiv.org/abs/2506.12365

Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics
This survey paper outlines the key developments in the field of Large Language Models (LLMs), such as enhancing their reasoning skills, adaptability to various tasks, increased computational efficiency, and ability to make ethical decisions. The techniques that have been most effective in bridging the gap between human and machine communications include the Chain-of-Thought prompting, Instruction Tuning, and Reinforcement Learning from Human Feedback. The improvements in multimodal learning and…

Real-Time Capable, Low-latency Upstream Scheduling in Multi-Tenant, SLA Compliant TWDM PON
Arijeet Ganguli, Marco Ruffini
https://arxiv.org/abs/2506.12118 …

Real-Time Capable, Low-latency Upstream Scheduling in Multi-Tenant, SLA Compliant TWDM PON
Virtualized Passive Optical Networks (vPONs) offer a promising solution for modern access networks, bringing enhanced flexibility, reduced capital expenditures (CapEx), and support for multi-tenancy. By decoupling network functions from physical infrastructure, vPONs enable service providers to efficiently share network resources among multiple tenants. In this paper, we propose a novel merging DBA algorithm, called the Dynamic Time and Wavelength Allocation (DTWA) algorithm, for a virtualized …

A Multi-Level Similarity Approach for Single-View Object Grasping: Matching, Planning, and Fine-Tuning
Hao Chen, Takuya Kiyokawa, Zhengtao Hu, Weiwei Wan, Kensuke Harada
https://arxiv.org/abs/2507.11938

A Multi-Level Similarity Approach for Single-View Object Grasping: Matching, Planning, and Fine-Tuning
Grasping unknown objects from a single view has remained a challenging topic in robotics due to the uncertainty of partial observation. Recent advances in large-scale models have led to benchmark solutions such as GraspNet-1Billion. However, such learning-based approaches still face a critical limitation in performance robustness for their sensitivity to sensing noise and environmental changes. To address this bottleneck in achieving highly generalized grasping, we abandon the traditional learn…

CLIP-HandID: Vision-Language Model for Hand-Based Person Identification
Nathanael L. Baisa, Babu Pallam, Amudhavel Jayavel
https://arxiv.org/abs/2506.12447

CLIP-HandID: Vision-Language Model for Hand-Based Person Identification
This paper introduces a new approach to person identification based on hand images, designed specifically for criminal investigations. The method is particularly valuable in serious crimes like sexual abuse, where hand images are often the sole identifiable evidence available. Our proposed method, CLIP-HandID, leverages pre-trained foundational vision-language model, particularly CLIP, to efficiently learn discriminative deep feature representations from hand images given as input to the image …

LARGO: Low-Rank Regulated Gradient Projection for Robust Parameter Efficient Fine-Tuning
Haotian Zhang, Liu Liu, Baosheng Yu, Jiayan Qiu, Yanwei Ren, Xianglong Liu
https://arxiv.org/abs/2506.12394

LARGO: Low-Rank Regulated Gradient Projection for Robust Parameter Efficient Fine-Tuning
The advent of parameter-efficient fine-tuning methods has significantly reduced the computational burden of adapting large-scale pretrained models to diverse downstream tasks. However, existing approaches often struggle to achieve robust performance under domain shifts while maintaining computational efficiency. To address this challenge, we propose Low-rAnk Regulated Gradient Projection (LARGO) algorithm that integrates dynamic constraints into low-rank adaptation methods. Specifically, LARGO …

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Boris Ivanovic, Cristiano Saltori, Yurong You, Yan Wang, Wenjie Luo, Marco Pavone
https://arxiv.org/abs/2506.12251

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their scalability and potential to leverage internet-scale pretraining for generalization. Accordingly, tokenizing sensor data efficiently is paramount to ensuring the real-time feasibility of such architectures on embedded hardware. To this end, we present an efficient triplane-based multi-camera tokenization strategy that leverages recent advances in 3D ne…