arXiv:2602.11163v1 Announce Type: new Abstract: Named Entity Recognition (NER) is an important task in natural language processing that aims to identify and extract key entities from unstructured text. We present a novel application of NER in plasma physics research articles and address the challenges of extracting specialized entities from scientific text in this domain. Research articles in plasma physics often contain highly complex and context-rich content that must be extracted to enable, e.g., advanced search. We propose a […]

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arXiv:2601.00163v1 Announce Type: new Abstract: Robotic fleets such as unmanned aerial and ground vehicles have been widely used for routine inspections of static environments, where the areas of interest are known and planned in advance. However, in many applications, such areas of interest are unknown and should be identified online during exploration. Thus, this paper considers the problem of simultaneous exploration, inspection of unknown environments and then real-time communication to a mobile ground control station to report the […]

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The rise of smart manufacturing under Industry 4.0 introduces mass customization and dynamic production, demanding more advanced and flexible scheduling techniques. The flexible job-shop scheduling problem (FJSP) has attracted significant attention due to its complex constraints and strong alignment with real-world production scenarios. Current deep reinforcement learning (DRL)-based approaches to FJSP predominantly employ constructive methods. While effective, they often fall short of reaching (near-)optimal solutions. In contrast, improvement-based methods iteratively explore the neighborhood of initial solutions and are […]

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arXiv:2306.06581v2 Announce Type: replace Abstract: Sinkhorn algorithm has been used pervasively to approximate the solution to optimal transport (OT) and unbalanced optimal transport (UOT) problems. However, its practical application is limited due to the high computational complexity. To alleviate the computational burden, we propose a novel importance sparsification method, called Spar-Sink, to efficiently approximate entropy-regularized OT and UOT solutions. Specifically, our method employs natural upper bounds for unknown optimal transport plans to establish effective sampling probabilities, and constructs […]

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arXiv:2602.07212v1 Announce Type: new Abstract: Although recent traffic benchmarks have advanced multimodal data analysis, they generally lack systematic evaluation aligned with official safety standards. To fill this gap, we introduce RoadSafe365, a large-scale vision-language benchmark that supports fine-grained analysis of traffic safety from extensive and diverse real-world video data collections. Unlike prior works that focus primarily on coarse accident identification, RoadSafe365 is independently curated and systematically organized using a hierarchical taxonomy that refines and extends foundational definitions of […]

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As institutional blockchain adoption hits a $933M market cap, discover why Ethereum, Hedera, and RYT have moved from pilot projects to the core of national digital identity and CBDC ecosystems. The pivot from speculative madness to sovereign infrastructure is no longer a projection; it is a line item in national budgets. While retail traders spent years chasing animal-themed tokens, the public sector quietly began rebuilding the foundations of civic trust. By 2026, the global blockchain government market is […]

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:::info Astounding Stories of Super-Science October, 1994, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. The Picture of Dorian Gray – Chapter V Astounding Stories of Super-Science October 1994: The Picture of Dorian Gray – Chapter V By Oscar Wilde ::: “Mother, Mother, I am so happy!” whispered the girl, burying her face in the lap of the faded, tired-looking woman who, with back turned to […]

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arXiv:2602.00913v1 Announce Type: new Abstract: Sentence-level human value detection is typically framed as multi-label classification over Schwartz values, but it remains unclear whether Schwartz higher-order (HO) categories provide usable structure. We study this under a strict compute-frugal budget (single 8 GB GPU) on ValueEval’24 / ValuesML (74K English sentences). We compare (i) direct supervised transformers, (ii) HO$rightarrow$values pipelines that enforce the hierarchy with hard masks, and (iii) Presence$rightarrow$HO$rightarrow$values cascades, alongside low-cost add-ons (lexica, short context, topics), label-wise threshold […]

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