arXiv:2603.12478v1 Announce Type: new Abstract: Multimodal instruction tuning is often compute-inefficient because training budgets are spread across large mixed image-video pools whose utility is highly uneven. We present Goal-Driven Data Optimization (GDO), a framework that computes six sample descriptors for each candidate and constructs optimized 1$times$ training subsets for different goals. Under a fixed one-epoch Qwen3-VL-8B-Instruct training and evaluation recipe on 8 H20 GPUs, GDO uses far fewer training samples than the Uni-10x baseline while converging faster and […]

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arXiv:2601.08977v1 Announce Type: new Abstract: Traditional two-dimensional thermography, despite being non-invasive and useful for defect detection in the construction field, is limited in effectively assessing complex geometries, inaccessible areas, and subsurface defects. This paper introduces Thermo-LIO, a novel multi-sensor system that can enhance Structural Health Monitoring (SHM) by fusing thermal imaging with high-resolution LiDAR. To achieve this, the study first develops a multimodal fusion method combining thermal imaging and LiDAR, enabling precise calibration and synchronization of multimodal data […]

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If I asked a hundred people to define twenty words, no two persons would give identical definitions for all twenty. If each word has just three possible interpretations (the actual number is far higher), that’s 3^20 = 3.4 billion possible combinations. Your definition of “intelligence” was shaped by every smart and stupid person you’ve met, every test you’ve taken, every moment you felt quick or slow. Mine was shaped by different people, different tests, different moments. When you […]

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Written from the perspective of a senior engineer who has built, debugged, and battle-tested operators in production. Table of Contents Why Operators Exist The Conceptual Foundation: Control Theory Kubernetes API Machinery: The Backbone Custom Resource Definitions (CRDs) The Controller Runtime: Inside the Engine Informers, Listers, and the Cache The Reconciliation Loop in Depth Work Queues and Rate Limiting Watches, Events, and Predicates Ownership, Finalizers, and Garbage Collection Status Subresource and Conditions Generation vs ObservedGeneration: A Deep Dive Concurrency, […]

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arXiv:2602.06204v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a standard tool for parameter-efficient finetuning of large models. While it induces a small memory footprint, its training dynamics can be surprisingly complex as they depend on several hyperparameters such as initialization, adapter rank, and learning rate. In particular, it is unclear how the optimal learning rate scales with adapter rank, which forces practitioners to re-tune the learning rate whenever the rank is changed. In this paper, we introduce […]

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Hybrid modeling, the combination of machine learning models and scientific mathematical models, enables flexible and robust data-driven prediction with partial interpretability. However, effectively the scientific models may be ignored in prediction due to the flexibility of the machine learning model, making the idea of hybrid modeling pointless. Typically some regularization is applied to hybrid model learning to avoid such a failure case, but the formulation of the regularizer strongly depends on model architectures and domain knowledge. In this […]

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arXiv:2602.06154v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale large language models efficiently by sparsely activating experts, but once an expert is selected, it is executed fully. Hence, the trade-off between accuracy and computation in an MoE model typically exhibits large discontinuities. We propose Mixture of Slimmable Experts (MoSE), an MoE architecture in which each expert has a nested, slimmable structure that can be executed at variable widths. This enables conditional computation not only over which experts are […]

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Every entrepreneur talks about vision, resilience, and execution. But beneath all of these traits lies a quieter, less visible skill that ultimately determines success or failure: decision-making under uncertainty. Markets shift, data is incomplete, and outcomes are rarely guaranteed. The leaders who endure are not those who wait for certainty—but those who learn how to think clearly without it. According to Alessio Vinassa, serial entrepreneur and business advisor, uncertainty is not an obstacle to leadership—it is the environment […]

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The Fifth Fourth Postulate of Decision Theory In 1820, the Hungarian mathematician Farkas Bolyai wrote a desperate letter to his son János, who had become consumed by the same problem that had haunted his father for decades: “You must not attempt this approach to parallels. I know this way to the very end. I have traversed this bottomless night, which extinguished all light and joy in my life. I entreat you, leave the science of parallels alone… Learn […]

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