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Doc: Amazon's Q Business AI assistant struggled with accuracy and data processing in its first year, drawing complaints; Amazon says the document is outdated (Eugene Kim/Business Insider)
https://www.businessinsider.com/amazon-q-significan…

Amazon internal review found its AI tool Q fell 'significantly' behind rivals on accuracy in its first year
Amazon's AI productivity tool Q Business faced significant accuracy challenges in its first year, leading to customer complaints and service updates.

The Steiner Path Aggregation Problem
Da Qi Chen, Daniel Hathcock, D Ellis Hershkowitz, R. Ravi
https://arxiv.org/abs/2510.01392 https://arxiv.org/pdf/2510.…

The Steiner Path Aggregation Problem
In the Steiner Path Aggregation Problem, our goal is to aggregate paths in a directed network into a single arborescence without significantly disrupting the paths. In particular, we are given a directed multigraph with colored arcs, a root, and $k$ terminals, each of which has a monochromatic path to the root. Our goal is to find an arborescence in which every terminal has a path to the root, and its path does not switch colors too many times. We give an efficient algorithm that finds such a s…

Hybrid biphoton spectrometer for time-resolved quantum spectroscopy across visible and near-infrared regions
Ozora Iso, Koya Onoda, Nicola J. Fairbairn, Masahiro Yabuno, Hirotaka Terai, Shigehito Miki, Ryosuke Shimizu
https://arxiv.org/abs/2510.01836

Hybrid biphoton spectrometer for time-resolved quantum spectroscopy across visible and near-infrared regions
Joint spectral measurements are a powerful tool for characterising biphoton spectral correlation, which is crucial for quantum information and communication technologies. In these applications, highly pure biphoton states are essential in any time- and frequency-mode, often obviating the need for time-resolved measurements. Conversely, spectroscopy utilising entangled photon pairs is gaining significant attention for its ability to unveil molecular dynamics, a field that critically demands time…

On The Road - To Xi’An 🗿
在路上 - 去西安 🗿
📷 Minolta Hi-Matic AF
🎞️Kentmere Pan 200
#filmphotography #Photography #blackandwhite

Jaylen Warren contract: Steelers RB agrees to two-year extension, eyes more touches in new-look backfield

https://www.cbssports.com/nfl/news/jaylen-

EgoTouch: On-Body Touch Input Using AR/VR Headset Cameras
Vimal Mollyn, Chris Harrison
https://arxiv.org/abs/2509.01786 https://arxiv.org/pdf/2509.01786

EgoTouch: On-Body Touch Input Using AR/VR Headset Cameras
In augmented and virtual reality (AR/VR) experiences, a user's arms and hands can provide a convenient and tactile surface for touch input. Prior work has shown on-body input to have significant speed, accuracy, and ergonomic benefits over in-air interfaces, which are common today. In this work, we demonstrate high accuracy, bare hands (i.e., no special instrumentation of the user) skin input using just an RGB camera, like those already integrated into all modern XR headsets. Our results show t…

RF-DETR for Robust Mitotic Figure Detection: A MIDOG 2025 Track 1 Approach
Piotr Giedziun, Jan So{\l}tysik, Mateusz G\'orczany, Norbert Ropiak, Marcin Przymus, Piotr Krajewski, Jaros{\l}aw Kwiecie\'n, Artur Bartczak, Izabela Wasiak, Mateusz Maniewski
https://arxiv.org/abs/2509.02599

RF-DETR for Robust Mitotic Figure Detection: A MIDOG 2025 Track 1 Approach
Mitotic figure detection in histopathology images remains challenging due to significant domain shifts across different scanners, staining protocols, and tissue types. This paper presents our approach for the MIDOG 2025 challenge Track 1, focusing on robust mitotic figure detection across diverse histological contexts. While we initially planned a two-stage approach combining high-recall detection with subsequent classification refinement, time constraints led us to focus on optimizing a single…

Biomarkers selection and combination based on the weighted Youden index
Ao Sun, Zhanwang Deng, Jiahui Zhao, Hang Li, Xiao-Hua Zhou
https://arxiv.org/abs/2509.02090 https://

Biomarkers selection and combination based on the weighted Youden index
In clinical practice, multiple biomarkers are used for disease diagnosis, but their individual accuracies are often suboptimal, with only a few proving directly relevant. Effectively selecting and combining biomarkers can significantly improve diagnostic accuracy. Existing methods often optimize metrics like the Area Under the ROC Curve (AUC) or the Youden index. However, optimizing AUC does not yield estimates for optimal cutoff values, and the Youden index assumes equal weighting of sensitivi…

AuditAgent: Expert-Guided Multi-Agent Reasoning for Cross-Document Fraudulent Evidence Discovery
Songran Bai, Bingzhe Wu, Yiwei Zhang, Chengke Wu, Xiaolong Zheng, Yaze Yuan, Ke Wu, Jianqiang Li
https://arxiv.org/abs/2510.00156

AuditAgent: Expert-Guided Multi-Agent Reasoning for Cross-Document Fraudulent Evidence Discovery
Financial fraud detection in real-world scenarios presents significant challenges due to the subtlety and dispersion of evidence across complex, multi-year financial disclosures. In this work, we introduce a novel multi-agent reasoning framework AuditAgent, enhanced with auditing domain expertise, for fine-grained evidence chain localization in financial fraud cases. Leveraging an expert-annotated dataset constructed from enforcement documents and financial reports released by the China Securit…

A Neuro-Fuzzy System for Interpretable Long-Term Stock Market Forecasting
Miha O\v{z}bot, Igor \v{S}krjanc, Vitomir \v{S}truc
https://arxiv.org/abs/2510.00960 https://

A Neuro-Fuzzy System for Interpretable Long-Term Stock Market Forecasting
In the complex landscape of multivariate time series forecasting, achieving both accuracy and interpretability remains a significant challenge. This paper introduces the Fuzzy Transformer (Fuzzformer), a novel recurrent neural network architecture combined with multi-head self-attention and fuzzy inference systems to analyze multivariate stock market data and conduct long-term time series forecasting. The method leverages LSTM networks and temporal attention to condense multivariate data into i…