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techtimes.com · Nov 3

GDPx Benchmark: Best Frontier AI Scores 12% on Real Work, Zero on Finance and Legal

SemiAnalysis’s GDPx benchmark tested 13 frontier AI models on 206 real professional tasks. Best score: 12%. Finance and legal returned zero across every model.

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arXiv

Nov 2

Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation

General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, creating mismatches that limit the capabilities of the complete system. We present Pixel, a co-designed full-stack system for learning general-purpose mobile manipulation. Pixel combines a low-cost wheeled humanoid with human-aligned kinematics and compliant grippers, multiple teleoperation and robot-free human data-collection interfaces, a unified whole-body controller, and a common policy learning pipeline across human and robot demonstrations. A hierarchical learning stack further enables language-conditioned visuomotor control and long-horizon task execution. We evaluate the system across hardware, data collection, and policy learning, and demonstrate mobile-manipulation behaviors requiring dexterity, active perception, navigation, and whole-body coordination. We hope that Pixel provides an integrated and extensible foundation for studying how robot hardware, data, control, and learning can be designed together for robot learning. More…

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arXiv

Sep 18

Beetle: A Bilingual Model Suite for Modelling Second-Language Processing

Bilingual language models (LMs) offer a controlled setting for studying how training conditions shape second-language (L2) behaviour, but prior work typically varies exposure structure, scale, and architecture at once, making it difficult to attribute effects to any single…

arXiv

Sep 18

Classification with Abstention Under Class-Conditional Error Constraints

We study binary classification with abstention under separate class-conditional error constraints, with the objective of minimizing abstention while keeping both errors below prescribed thresholds. We characterize the distribution-free minimax rate of excess abstention risk, up…

arXiv

Sep 18

X-Beat: An Explainable Framework for ECG Image Classification

Accurate automated interpretation of electrocardio- grams (ECGs) is essential for early detection of cardiac condi- tions such as myocardial infarction and rhythm abnormalities. However, many high-performing deep learning models remain difficult to deploy in clinical settings…

arXiv

Sep 18

FlashDiffusion: Fused Tiled Kernel Spectral Decomposition

Diffusion maps, and kernel methods more generally, provide an interpretable nonlinear spectral representation basis for geometric learning. In the geometric limit, small bandwidth, these matrices tend to be high rank and thus require materializing dense Gaussian kernels…

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