arXiv:2602.12311v1 Announce Type: new Abstract: We present a multi-agent framework for generating physics simulation code from natural language descriptions, featuring a novel perceptual self-reflection mechanism for validation. The system employs four specialized agents: a natural language interpreter that converts user requests into physics-based descriptions; a technical requirements generator that produces scaled simulation parameters; a physics code generator with automated self-correction; and a physics validator that implements perceptual self-reflection. The key innovation is perceptual validation, which analyzes rendered animation […]

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Table of Links Abstract and 1. Introduction Some recent trends in theoretical ML 2.1 Deep Learning via continuous-time controlled dynamical system 2.2 Probabilistic modeling and inference in DL 2.3 Deep Learning in non-Euclidean spaces 2.4 Physics Informed ML Kuramoto model 3.1 Kuramoto models from the geometric point of view 3.2 Hyperbolic geometry of Kuramoto ensembles 3.3 Kuramoto models with several globally coupled sub-ensembles Kuramoto models on higher-dimensional manifolds 4.1 Non-Abelian Kuramoto models on Lie groups 4.2 Kuramoto models […]

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San Salvador, El Salvador, 28 January 2026 — Bitget Wallet has made a strategic shift into an all-in-one everyday finance app, refreshing its interface to place payments at the center of the app experience. The move follows the wallet surpassing 90 million users globally, highlighting the need to support more frequent, real-world financial activity at scale. It reflects a broader transition as crypto wallets move beyond investment-led use cases into daily financial accounts for spending, sending, saving, and […]

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arXiv:2601.18908v1 Announce Type: new Abstract: Speech Emotion Recognition systems often use static features like Mel-Frequency Cepstral Coefficients (MFCCs), Zero Crossing Rate (ZCR), and Root Mean Square Energy (RMSE). Because of this, they can misclassify emotions when there is acoustic noise in vocal signals. To address this, we added dynamic features using Dynamic Spectral features (Deltas and Delta-Deltas) along with the Kalman Smoothing algorithm. This approach reduces noise and improves emotion classification. Since emotion changes over time, the Kalman […]

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Zhipu AI and Huawei just dropped GLM-Image, and the technical details are interesting. First multimodal model trained completely on Chinese chips (Huawei Ascend 910) from data preprocessing to full scale training. They’re using a hybrid architecture combining autoregressive + diffusion decoder. What stands out is the Chinese text rendering. It consistently ranks first among open source models for complex text generation, especially handling Chinese characters which most models struggle with. Native support for 1024 to 2048 resolution at […]

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arXiv:2601.06147v1 Announce Type: cross Abstract: Meta-learning methods for regression like Neural (Diffusion) Processes achieve impressive results, but with these models it can be difficult to incorporate expert prior knowledge and information contained in metadata. Large Language Models (LLMs) are trained on giant corpora including varied real-world regression datasets alongside their descriptions and metadata, leading to impressive performance on a range of downstream tasks. Recent work has extended this to regression tasks and is able to leverage such prior […]

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arXiv:2601.16985v1 Announce Type: new Abstract: Adapting to unforeseen novelties in open-world environments remains a major challenge for autonomous systems. While hybrid planning and reinforcement learning (RL) approaches show promise, they often suffer from sample inefficiency, slow adaptation, and catastrophic forgetting. We present a neuro-symbolic framework integrating hierarchical abstractions, task and motion planning (TAMP), and reinforcement learning to enable rapid adaptation in robotics. Our architecture combines symbolic goal-oriented learning and world model-based exploration to facilitate rapid adaptation to environmental […]

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