In this paper we investigate forecasting coevolving time series that feature intricate dependencies and nonstationary dynamics by using an LLM Large Language Models approach We propose a novel modeling approach named ContextAware ARLLM CAARL that provides an interpretable framework to decode the contextual dynamics influencing changes in coevolving series CAARL decomposes time series into autoregressive segments constructs a temporal dependency graph and serializes this graph into a narrative to allow processing by LLM This design yields a chainofthoughtlike […]

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arXiv:2601.09894v1 Announce Type: new Abstract: We introduce the one-cold Poisson channel (OCPC), where the transmitter chooses one of several frequency bands to attenuate at a time. In particular, the perfect OCPC, where the number of bands is unlimited, is an extremely simple continuous-time memoryless channel. It has a capacity 1, zero channel dispersion, and an information spectrum being the degenerate distribution at 1. It is the only known nontrivial (discrete or continuous-time) memoryless channel with a closed-form formula […]

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An autonomous table tennis robot developed by Sony AI has competed against and defeated high-level human players in regulated matches, according to Reuters. The system is part of a broader category often referred to as “physical AI,” where artificial intelligence is applied to machines operating in real-world environments. The robot, named Ace, was designed to operate in a competitive sport environment that requires rapid decision-making and precise motor control. According to the project team, it combines high-speed perception […]

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Reinforcement Learning with Verifiable Rewards (RLVR) has become the leading paradigm for enhancing reasoning in Large Language Models (LLMs). However, standard RLVR algorithms suffer from a well-documented pathology: while they improve Pass@1 accuracy through sharpened sampling, they simultaneously narrow the model’s reasoning boundary and reduce generation diversity. We identify a root cause that existing methods overlook: the uniform penalization of errors. Current approaches — whether data-filtering methods that select prompts by difficulty, or advantage normalization schemes — treat […]

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arXiv:2601.00189v1 Announce Type: new Abstract: Mosquitos are the main transmissive agents of arboviral diseases. Manual classification of their neuronal spike patterns is very labor-intensive and expensive. Most available deep learning solutions require fully labeled spike datasets and highly preprocessed neuronal signals. This reduces the feasibility of mass adoption in actual field scenarios. To address the scarcity of labeled data problems, we propose a new Generative Adversarial Network (GAN) architecture that we call the Semi-supervised Swin-Inspired GAN (SSI-GAN). The […]

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Did anyone get an email? I emailed the chairs. They say every participant got an email titled: “CVPR26 BP Scholarship Decision Has Been Released”, and participants got a separate email with the award and details. But I got no such email, yet. submitted by /u/Erika_bomber [link] [comments]

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arXiv:2604.13204v1 Announce Type: new Abstract: The motion planning problem requires finding a collision-free path between start and goal configurations in high-dimensional, cluttered spaces. Recent learning-based methods offer promising solutions, with self-supervised physics-informed approaches such as Neural Time Fields (NTFields) solving the Eikonal equation to learn value functions without expert demonstrations. However, existing physics-informed methods struggle to scale in complex, multi-room environments, where simply increasing the number of samples cannot resolve local minima or guarantee global consistency. We propose […]

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Built a reservoir computing system (Liquid State Machine) as a learning experiment. Instead of a standard static reservoir, I added biological simulation layers on top to see how constraints affect behavior. What it actually does (no BS): – LSM with 2000+ reservoir neurons, Numba JIT-accelerated – Hebbian + STDP plasticity (the reservoir rewires during runtime) – Neurogenesis/atrophy reservoir can grow or shrink neurons dynamically – A hormone system (3 floats: dopamine, cortisol, oxytocin) that modulates learning rate, reflex […]

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