Every developer who’s built an IoT pipeline has hit this wall: the code that worked beautifully with ten sensors publishing once per second collapses under production load. Your database starts lagging, the message queue backs up, and suddenly you’re troubleshooting at 2 AM trying to figure out why 5000 devices at 1Hz brought everything to its knees. Your code is fine. The broker config is fine. The architecture isn’t. MQTT streams data continuously; SQL databases thrive on batched writes. Most tutorials […]

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arXiv:2603.06703v1 Announce Type: new Abstract: Graph databases are widely used in systems that manage rich metadata, yet current modelling practices often embed descriptive attributes directly in nodes, leading to redundancy and inconsistent semantics. This paper introduces the Fifth Graph Normal Form (5GNF), a trait-based normalization framework for property graphs that represents recurring metadata as canonical Trait Nodes connected through HAS_TRAIT relationships. We formalize trait functional dependencies (tFDs) and present the TraitExtraction5GNF algorithm for identifying and extracting reusable traits. […]

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I’m working on a startup right now and from the outside it probably looks like I’m doing fine, but internally it feels like I’m always late to something late to trends late to execution and I can’t tell if that feeling is actually useful (like pushing me to move faster) or if it’s just messing with my ability to focus for people who’ve been through this, does that ever go away? or do you just learn how to […]

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I’m writing a series called “Roads to a Universal World Model”. I think this is arguably the most consequential open problem in AI and robotics right now, and most coverage either hypes it as “the next LLM” or buries it in survey papers. I’m trying to do something different: trace each major path from origin to frontier, then look at where they converge and where they disagree. The approach is narrative-driven. I trace the people and decisions behind […]

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The following workflow is a conclusion of the video: from Mu Li of Amazon flowchart TB next(“another paper”) subgraph p1 [“Pass 1(Selection)”] direction LR title[Title] abs[Abstract] conc[Conclusion] FaT[“Figures and Tablets”] title–abs–conc– FaT end p1.- dec{Decision}.-|”stop(low quality ornlow relation)”| next dec.-|”go on”| p2 subgraph p2 [“Pass 2(Selection)”] direction TB int_cit[“Introduction:nSome important Citations” ] method_ME[“Method:nwithout Math and Engineeringnfocus on figures and tablets”] end p2.-dec2{Decision} dec2.-|”too hard to understand,n go to one ofn the citationsnin introduction”

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arXiv:2603.00632v1 Announce Type: new Abstract: Semantic IDs (SIDs) are compact discrete representations derived from multimodal item features, serving as a unified abstraction for ID-based and generative recommendation. However, learning high-quality SIDs remains challenging due to two issues. (1) Collision problem: the quantized token space is prone to collisions, in which semantically distinct items are assigned identical or overly similar SID compositions, resulting in semantic entanglement. (2) Collision-signal heterogeneity: collisions are not uniformly harmful. Some reflect genuine conflicts between […]

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arXiv:2602.23581v1 Announce Type: new Abstract: Multivariate time series forecasting is widely applied in fields such as transportation, energy, and finance. However, the data commonly suffers from issues of multi-scale characteristics, weak correlations, and noise interference, which limit the predictive performance of existing models. This paper proposes a dual-stream sparse Mixer prediction framework that extracts global trends and local dynamic features from sequences in both the frequency and time domains, respectively. It employs a sparsity mechanism to filter out […]

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arXiv:2506.13107v3 Announce Type: replace-cross Abstract: Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and public policy. A standard modeling practice with this method is honest estimation: dividing the data into two samples, one to define subgroups and another to estimate treatment effects within them. This is intended to reduce overfitting and is the default in many software packages. But is it the right choice? In this paper, we show […]

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arXiv:2601.15307v1 Announce Type: new Abstract: The rapid development of automated scientific survey generation technology has made it increasingly important to establish a comprehensive benchmark to evaluate the quality of generated surveys.Nearly all existing evaluation benchmarks rely on flawed selection criteria such as citation counts and structural coherence to select human-written surveys as the ground truth survey datasets, and then use surface-level metrics such as structural quality and reference relevance to evaluate generated surveys.However, these benchmarks have two key […]

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