arXiv:2603.15771v1 Announce Type: new Abstract: Autonomous driving requires safe planning, but most learning-based planners lack explicit self-correction ability: once an unsafe action is proposed, there is no mechanism to correct it. Thus, we propose CorrectionPlanner, an autoregressive planner with self-correction that models planning as motion-token generation within a propose, evaluate, and correct loop. At each planning step, the policy proposes an action, namely a motion token, and a learned collision critic predicts whether it will induce a collision […]

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Singapore – Blockman PR –  JANUARY 30, 2026 – Bitget Token (BGB) is now available for trading on Kraken, marking its first major regulated U.S. exchange listing and an important step in expanding global access to the token. The listing brings BGB onto one of the industry’s most established exchanges, improving liquidity and making the asset more accessible across global markets. As onchain finance scales, the way crypto assets are evaluated is changing. Focus is shifting toward tokens […]

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arXiv:2603.24606v1 Announce Type: new Abstract: We present a method for estimating the number of distinct values (NDV) of a column in columnar file formats, using only existing file metadata–no extra storage, no data access. Two complementary signals are exploited: (1)~inverting the dictionary-encoded storage size equation yields accurate NDV estimates when distinct values are well-spread across row groups; (2)~counting distinct min/max values across row groups and inverting a coupon collector model provides robust estimates for sorted or partitioned data. […]

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The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approximation theory provide quantitative approximation rates for ReLU networks on the class of $α$-Hölder functions $f: [0,1]^N to mathbb{R}$. The goal of this paper is to provide similar quantitative approximation results in the context of group equivariant learning, where the learned $α$-Hölder function is known to obey certain group symmetries. While there has been much interest in the […]

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In any analysis project, raw tables of numbers often don’t tell the full story. Visualisations simplify complexity by transforming data into shapes that our brains can quickly understand, emphasising trends, outliers, and regime shifts that might be overlooked in raw data. This is especially vital in finance and trading, where clear visuals can uncover risks, opportunities, and patterns, directly affecting decisions on position sizing, timing, and confidence. Today, we will use FMP APIs to interpret earnings data: extracting […]

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arXiv:2602.02585v1 Announce Type: new Abstract: Modern enterprise systems exhibit complex interdependencies that make observability and incident response increasingly challenging. Manual alert triage, which typically involves log inspection, API verification, and cross-referencing operational knowledge bases, remains a major bottleneck in reducing mean recovery time (MTTR). This paper presents an agentic observability framework deployed within Adobe’s e-commerce infrastructure that autonomously performs alert triage using a ReAct paradigm. Upon alert detection, the agent dynamically identifies the affected service, retrieves and analyzes […]

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This study develops a leakage-safe PCA–APT framework that constructs an idiosyncratic market-stress index from cross-sectional residual dispersion and evaluates its usefulness for anticipating equity drawdowns. Using daily adjusted prices for SPY and 11 U.S. sector ETFs from 2020–2025, we compute sector excess returns (sector minus SPY), estimate a low-dimensional common component via principal component analysis (PCA), and define residual stress as the cross-sectional root-mean-square magnitude of PCA reconstruction residuals. To prevent look-ahead bias, the PCA mapping is estimated […]

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We rolled out zero-trust architecture across 60 microservices — mTLS, SPIRE workload identity, OPA policy enforcement, no static credentials. Security incidents dropped 87%. Deploy frequency dropped 34%, mean deploy time doubled from 22 to 47 minutes, and we burned roughly $340K in engineering productivity in year one. The mistake wasn’t adopting zero-trust. It was treating it as a security project instead of a developer experience project. Start policies in warn mode, decouple certificate rotation from your deploy pipeline, […]

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arXiv:2602.21334v1 Announce Type: new Abstract: As satellites have proliferated, interest has increased in autonomous rendezvous, proximity operations, and docking (ARPOD). A fundamental challenge in these tasks is the uncertainties when operating in space, e.g., in measurements of satellites’ states, which can make future states difficult to predict. Another challenge is that satellites’ onboard processors are typically much slower than their terrestrial counterparts. Therefore, to address these challenges we propose to solve an ARPOD problem with feedback optimization, which […]

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