Last week, a post about my open-source project CocoIndex Code hit 54K+ views on X after @RoundtableSpace shared it. The tweet was simple: “CocoIndex Code gives your coding agent a brain.” That one line captured exactly what we built and why it matters. The problem is straightforward. Every time your AI coding agent needs context about your codebase, it pulls in entire files. Function signatures, import statements, docstrings, blank lines, comments you wrote at 2am — everything gets […]

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Software-Defined Network (SDN) renders flexible traffic engineering, but consumes a lot of energy. There is an overhead on the control-plane because of flow-rule updates are done always and the energy consumption by the forwarding hardware. Current energy-aware SDN methods mostly focus on static or greedy optimisations. This can cause too many Ternary Content-Addressable Memory (TCAM) updates and unstable rule churn when traffic changes over time. This article introduces a Dynamic Flow Rule Placement (DFRP) framework for real-time energy […]

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arXiv:2602.20372v1 Announce Type: new Abstract: Recent research argues that exact recursive numeral systems optimize communicative efficiency by balancing a tradeoff between the size of the numeral lexicon and the average morphosyntactic complexity (roughly length in morphemes) of numeral terms. We argue that previous studies have not characterized the data in a fashion that accounts for the degree of complexity languages display. Using data from 52 genetically diverse languages and an annotation scheme distinguishing between predictable and unpredictable allomorphy […]

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Reliable agentic AI requires not only accurate reasoning and adaptive control, but also mechanisms that preserve reliability over time. While recent work has introduced system-level evaluation frameworks (e.g., HB-Eval) and real-time control architectures (e.g., Adapt-Plan), the question of how reliability is retained across an agent’s operational lifespan remains largely unaddressed. Existing memory mechanisms typically store experiences based on recency or salience, inadvertently allowing low-quality behaviors to accumulate and degrade long-term performance.This paper introduces Evaluation-Driven Memory (EDM), a persistence […]

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arXiv:2604.22754v1 Announce Type: new Abstract: No standardized benchmark exists for evaluating OCR on food packaging, despite its critical role in automated halal food verification. Existing benchmarks target documents or scene text, missing the unique challenges of ingredient labels: curved surfaces, dense multilingual text, and sub-8pt fonts. We present HalalBench, the first open multilingual benchmark for food packaging OCR, comprising 1,043 images (50 real, 993 synthetic) with 36,438 annotations in COCO format spanning 14 languages. We evaluate four engines: […]

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arXiv:2602.15950v1 Announce Type: new Abstract: We present a simple experiment that exposes a fundamental limitation in vision-language models (VLMs): the inability to accurately localize filled cells in binary grids when those cells lack textual identity. We generate fifteen 15×15 grids with varying density (10.7%-41.8% filled cells) and render each as two image types — text symbols (. and #) and filled squares without gridlines — then ask three frontier VLMs (Claude Opus, ChatGPT 5.2, and Gemini 3 Thinking) […]

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arXiv:2604.14163v1 Announce Type: new Abstract: Maritime distress communications transmitted over very high frequency (VHF) radio are safety-critical voice messages used to report emergencies at sea. Under the Global Maritime Distress and Safety System (GMDSS), such messages follow standardized procedures and are expected to convey essential details, including vessel identity, position, nature of the distress, and required assistance. In practice, however, automatic analysis remains difficult because distress messages are often brief, noisy, and produced under stress, may deviate from […]

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