arXiv:2602.00910v1 Announce Type: new Abstract: Deep learning has revolutionized medical image analysis, playing a vital role in modern clinical applications. However, the deployment of large-scale models in real-world clinical settings remains challenging due to high computational costs, latency constraints, and patient data privacy concerns associated with cloud-based processing. To address these bottlenecks, this review provides a comprehensive synthesis of efficient and lightweight deep learning architectures specifically tailored for the medical domain. We categorize the landscape of modern efficient […]

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arXiv:2604.20846v1 Announce Type: new Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolve at different temporal and spatial scales. Most existing methods compress a user’s history into a single latent representation, which tends to entangle heterogeneous signals such as routine mobility patterns, short-term intent, and temporal regularities. This entanglement limits the flexibility of state evolution and reduces the model’s ability to adapt to diverse decision contexts. We propose […]

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Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to catastrophic forgetting of previous knowledge. Existing methods typically treat parameters uniformly, failing to distinguish between specific task knowledge and shared capabilities. We introduce Mixture of Sparse Experts for Task Agnostic Continual Learning (SETA), a framework that resolves the plasticity-stability conflict through adaptive sparse subspace decomposition into task-specific expert modules. Unlike standard updates, where tasks compete for the same […]

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Separating the contributions of individual chromogenic stains in RGB histology whole slide images (WSIs) is essential for stain normalization, quantitative assessment of marker expression, and cell-level readouts in immunohistochemistry (IHC). Classical Beer-Lambert (BL) color deconvolution is well-established for two- or three-stain settings, but becomes under-determined and unstable for multiplex IHC (mIHC) with K>3 chromogens. We present a simple, data-driven encoder-decoder architecture that learns cohort-specific stain characteristics for mIHC RGB WSIs and yields crisp, well-separated per-stain concentration maps. The […]

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arXiv:2604.02344v1 Announce Type: new Abstract: WebGPU’s security-focused design imposes per-operation validation that compounds across the many small dispatches in neural network inference, yet the true cost of this overhead is poorly characterized. We present a systematic characterization of WebGPU dispatch overhead for LLM inference at batch size 1, spanning four GPU vendors (NVIDIA, AMD, Apple, Intel), two native implementations (Dawn, wgpu-native) and three browsers (Chrome, Safari, Firefox), and two model sizes (Qwen2.5-0.5B and 1.5B). Our primary contribution is […]

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Learning representative embeddings for different types of speaking styles, such as emotion, age, and gender, is critical for both recognition tasks (e.g., cognitive computing and human-computer interaction) and generative tasks (e.g., style-controllable speech generation). In this work, we introduce ParaMETA, a unified and flexible framework for learning and controlling speaking styles directly from speech. Unlike existing methods that rely on single-task models or cross-modal alignment, ParaMETA learns disentangled, task-specific embeddings by projecting speech into dedicated subspaces for each […]

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The foreign exchange market is really moving away from pure intuition and toward a space shaped by speed, data and precision. By using automated systems in your routine, you can approach volatility with a level of discipline that manual trading often struggles to maintain. Every entry and exit can be based on clear rules, not the emotional swings that frequently influence human decisions. Currency markets really move quickly, often faster than any person can react. With advanced digital […]

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arXiv:2601.08927v1 Announce Type: new Abstract: For any positive integer $g ge 2$, we derive general conditions for the existence of a $2g$-cycle in the Tanner graph of two-dimensional ($2$-D) classical quasi-cyclic (QC) low-density parity-check (LDPC) codes. Based on these conditions, we construct a family of $2$-D classical QC-LDPC codes with girth greater than $4$ by stacking $p times p times p$ tensors, where $p$ is an odd prime. Furthermore, for composite values of $p$, we propose two additional […]

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Large language models are reactive and user-centric, where if a user changes a prompt, the output changes. But research from Anthropic suggests that this basis alone is insufficient. In an in-depth explanation of Claude’s internal environment, the organization shows a hidden layer, the J Space, higher user input, and an important role in how Claude reasons and understands what to say. By depicting that internal edits to the space can change the results even without affecting the outer […]

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