Introduction In a fintech or wealthtech product, people constantly need quick market context. Why did this stock move. What changed recently. What should we watch next. Right now, this usually turns into manual work. Someone pulls recent returns, checks a couple fundamentals, scans headlines, then writes a short Slack or Notion note. It works, but it doesn’t scale, and every person formats it differently Dashboards help when the question is predefined. Pure LLM answers are flexible, but they’re […]

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arXiv:2602.13298v1 Announce Type: new Abstract: Increasing convolutional depth has been central to advances in image recognition, yet deeper networks do not uniformly yield higher accuracy, stable optimization, or efficient computation. We present a controlled comparative study of three canonical convolutional neural network architectures – VGG, ResNet, and GoogLeNet – to isolate how depth influences classification performance, convergence behavior, and computational efficiency. By standardizing training protocols and explicitly distinguishing between nominal and effective depth, we show that the benefits […]

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arXiv:2602.21365v1 Announce Type: new Abstract: Purpose: Curating large-scale datasets of operating room (OR) workflow, encompassing rare, safety-critical, or atypical events, remains operationally and ethically challenging. This data bottleneck complicates the development of ambient intelligence for detecting, understanding, and mitigating rare or safety-critical events in the OR. Methods: This work presents an OR video diffusion framework that enables controlled synthesis of rare and safety-critical events. The framework integrates a geometric abstraction module, a conditioning module, and a fine-tuned diffusion […]

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Self Engineering Reinforced Learning Framework Enterprise AI sovereignty for everyone. Off the grid. On the chain. 10 products. Open source the floor, sell the ceiling. Novel Patterns, tools, and templates Learn to build self-evolving systems Open source the floor. Sell the ceiling. Platform health across all hosting I would love the inputs of all on my new endevour, and have a happy Valentines Day everyone. SERLF submitted by /u/Glittering-Lead-2314 [link] [comments]

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Recent progress in reinforcement learning with verifiable rewards (RLVR) shows that small, specialized language models (SLMs) can exhibit structured reasoning without relying on large monolithic LLMs. We introduce soft hidden-state collaboration, where multiple heterogeneous frozen SLM experts are integrated through their internal representations via a trainable attention interface. Experiments on Reasoning Gym and GSM8K show that this latent integration is competitive with strong single-model RLVR baselines. Ablations further reveal a dual mechanism of expert utilization: for simpler arithmetic […]

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arXiv:2602.11175v1 Announce Type: new Abstract: Transformers have become the foundational architecture for a broad spectrum of sequence modeling applications, underpinning state-of-the-art systems in natural language processing, vision, and beyond. However, their theoretical limitations in discrete reasoning tasks, such as arithmetic, logical inference, and algorithmic composition, remain a critical open problem. In this survey, we synthesize recent studies from three theoretical perspectives: circuit complexity, approximation theory, and communication complexity, to clarify the structural and computational barriers that transformers face […]

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arXiv:2602.22280v1 Announce Type: new Abstract: Cardiovascular disease is the primary cause of death globally, necessitating early identification, precise risk classification, and dependable decision-support technologies. The advent of large language models (LLMs) provides new zero-shot and few-shot reasoning capabilities, even though machine learning (ML) algorithms, especially ensemble approaches like Random Forest, XGBoost, LightGBM, and CatBoost, are excellent at modeling complex, non-linear patient data and routinely beat logistic regression. This research predicts cardiovascular disease using a merged dataset of 1,190 […]

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