arXiv:2406.19958v2 Announce Type: replace Abstract: Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression model that is commonly used in causal inference and beyond. Its strong predictive performance is supported by well-developed estimation theory, comprising guarantees that its posterior distribution concentrates around the true regression function at optimal rates under various data generative settings and for appropriate prior choices. However, the computational properties of the widely-used BART sampler proposed by Chipman et al. (2010) are yet […]

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Artificial intelligence is making automation accelerate faster than previous waves. With AI as a propellant, the work of building automation increasingly becomes automatable itself. As it becomes cheaper and easier to mechanize tasks, automation spreads faster—and speeds up as it spreads. The result is that the current wave of AI adoption is likely to produce major disruption in the labor market. In earlier automation waves, the limiting factor was rarely whether a task could be automated in theory. The real […]

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arXiv:2602.09075v1 Announce Type: new Abstract: In-Context Learning (ICL) in transformers acts as an online associative memory and is believed to underpin their high performance on complex sequence processing tasks. However, in gated linear attention models, this memory has a fixed capacity and is prone to interference, especially for long sequences. We propose Palimpsa, a self-attention model that views ICL as a continual learning problem that must address a stability-plasticity dilemma. Palimpsa uses Bayesian metaplasticity, where the plasticity of […]

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Hey yall, I started working on this https://github.com/jimmie-jams/SilksongRL a while ago and finally managed to train an agent to beat one (1) boss. So, I figured it was time to share my glorious creation with the world. Jokes aside, I’d love to hear your thoughts! There are more environments/bosses already configured and it’s very easy to add new ones as well but I just don’t have the time/compute to train agents at a faster rate than I currently […]

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arXiv:2602.02526v1 Announce Type: new Abstract: The stability of generative artificial intelligence trained on recursive synthetic data is conventionally monitored via Perplexity (PPL). We demonstrate that PPL is a deceptive metric in context-stabilized regimes (L=128). Using a rigorous sliding-window protocol (N=1500), we identify a novel failure mode termed “Semantic Tunneling.” While the Baseline model maintains high grammatical fluency (PPL approx. 83.9), it suffers a catastrophic loss of semantic diversity, converging within seven generations to a single, low-entropy narrative attractor: […]

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arXiv:2603.00555v1 Announce Type: new Abstract: Skill-based programming of robots provides a flexible approach for automation. Existing solutions neglect the optimization of motion sequences, leading to inefficiencies in execution. This work introduces a planning method that enhances skill-based robot programming by integrating motion sequence optimization. This optimization leads to a new MoveContinuousSkill. The software for executing the MoveContinuousSkill is implemented on a Programmable Logic Controller and applied across multiple robotic systems. Experimental results demonstrate a significant improvement in execution […]

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arXiv:2511.06374v2 Announce Type: replace-cross Abstract: The one-epoch overfitting problem has drawn widespread attention, especially in CTR and CVR estimation models in search, advertising, and recommendation domains. These models which rely heavily on large-scale sparse categorical features, often suffer a significant decline in performance when trained for multiple epochs. Although recent studies have proposed heuristic solutions, the fundamental cause of this phenomenon remains unclear. In this work, we present a theoretical explanation grounded in Rademacher complexity, supported by empirical […]

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Netflix is rolling out a new live voting feature that lets viewers interact with live content in real time, as the company continues to experiment with more participatory formats. The feature will debut with the premiere of Netflix’s live-streamed talent show Star Search on January 20. Subscribers watching the show live will be able to vote on performances in two ways: by choosing from a multiple-choice menu or by rating contestants on a five-star scale. Voting can be […]

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arXiv:2603.10053v1 Announce Type: new Abstract: The Pickup and Delivery Problem (PDP) is a fundamental and challenging variant of the Vehicle Routing Problem, characterized by tightly coupled pickup–delivery pairs, precedence constraints, and spatial layouts that often exhibit clustering. Existing deep reinforcement learning (DRL) approaches either model all nodes on a flat graph, relying on implicit learning to enforce constraints, or achieve strong performance through inference-time collaborative search at the cost of substantial latency. In this paper, we propose emph{CAADRL} […]

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arXiv:2601.17053v1 Announce Type: new Abstract: Physical activity during hip fracture rehabilitation is essential for mitigating long-term functional decline in geriatric patients. However, it is rarely quantified in clinical practice. Existing continuous monitoring systems with commercially available wearable activity trackers are typically developed in middle-aged adults and therefore perform unreliably in older adults with slower and more variable gait patterns. This study aimed to develop a robust human activity recognition (HAR) system to improve continuous physical activity recognition in […]

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