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Pulse · forbes.com

forbes.com · Oct 29

Sequoia Bets On This $3 Billion Startup's Plan To Automate The Office

Companies like Ramp and Notion rely on Serval to automate mundane support tasks like password resets and app access.

Pulse · eu.36kr.com

eu.36kr.com · Oct 29

"North American Doubao" has become the world's most powerful model, and Google's market capitalization has dropped by more than 300 billion US dollars.

Beat AI, Lost Wall Street: Unveiling the Paradox of Outperforming Artificial Intelligence While Facing Setbacks in the Financial Hub. This in-depth analysis explores the real-world scenarios where market participants successfully outmaneuver advanced AI-driven trading systems, yet encounter unexpected failures and strategic missteps in the high-stakes Wall Street ecosystem. It delves into the core conflicts between human trading intuition, algorithmic limitations, market volatility, and…

Pulse

Top picks this weekarXiv

arXiv

Oct 27

Honeycomb-Surfels: Compact Hexagonal Primitives for Efficient Scene Rendering and Reconstruction

Novel view synthesis and 3D reconstruction have advanced rapidly with radiance fields and splatting, yet their memory and computational demands limit their use in resource-constrained settings. We introduce Hexels: novel planar hexagonal surface elements with a first-order spatial color field for efficient 3D scene and 2D image representation. Hexels exploit locally planar regions with smoothly varying appearance using fewer, larger primitives. Their hexagonal support provides an area- and boundary-efficient domain, while the local color field captures appearance variation within each primitive. Across 34 scenes, Hexels improve PSNR over memory-matched 2DGS by 4.53-7.38 dB across datasets while requiring lower training VRAM. We further ablate Hexels by showing that per primitive, Hexels outperform 2DGS by upto 4.74 dB while using lower training VRAM and having 2.31 times faster FPS. Even in unconstrained settings, Hexels offers complementary quality-memory trade-offs. For efficient 3D surface reconstruction, Hexels reduce error by 28.9% compared with memory-matched 2DGS across 15 DTU scans. On 6 Tanks and Temples surface scenes, Hexels achieves the highest mean F1 among compared…

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arXiv

Sep 18

CASCADE Against Jailbreaks: Combination Across Stages with Controlled Attack-Defense Evaluation

Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, but it remains unclear which defenses to deploy at each stage and how to combine them. Prior empirical studies, fragmented by…

arXiv

Sep 18

RegKT: Interpretable and Robust Deep Knowledge Tracing With IRT-Regularizer

As deep learning models continue to advance, knowledge tracing models have achieved higher accuracy. However, these gains come at the cost of reduced interpretability, which is crucial for practitioners in educational settings to adopt new methodologies. Additionally, deep…

arXiv

Sep 18

Per-Aetiology Contrastive Severity Embeddings with Phonological Pseudo-Labelling for Multilingual Dysarthric Speech

Most multilingual dysarthria-severity systems either train on a single aetiology-language pair or pool heterogeneous aetiologies into one label space. We test that pooling assumption with four matched HuBERT-base contrastive embedding models under a shared backbone, training…

arXiv

Sep 18

From Pretraining to Proficiency: Real-World Subtask RL for Long-Horizon Manipulation with Minimal Human Intervention

A pretrained robot foundation policy may execute most of a long-horizon task yet repeatedly fail at a few critical subtasks. Collecting additional full-task demonstrations for supervised fine-tuning (SFT) requires operators to repeat behaviors the policy already performs well.…

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