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@ETN

Emerging Technologies Papers

@ETN
New Emerging Technologies papers from arxiv.org: information processing based on alternatives t. Thank you to arXiv for use of its open access interoperability.
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  • @ETN
    Emerging Technologies Papers
    @ETN
    Sep 7
    Automated by @PremiumAccts
    Hatebench in the era of safer LLMs Ole Becker, Tobias Jongen, Philip Kolbe, Sonal Khosla, Vaibhav Bajpai arxiv.org/abs/2609.05169 [𝚌𝚜.𝙴𝚃]
    As Large Language Models (LLMs) lower the barrier for au- tomated content generation, the potential for producing hate speech poses a significant challenge for digital safety. This paper presents a reproducibility study of the HateBench paper by Shen et al., investigating whether existing hate speech detectors, typically trained on human-authored data, generalize to LLM-generated hateful content, and evaluating whether their reported weaknesses are stable over time and robust to evolving components. We independently reconstruct the original dataset genera- tion pipeline using modern LLMs and extend the benchmark to include recently released models and updated detector versions. Our independent assessment under current con- ditions finds that for newer LLMs, safeguards have been put into place to prevent the generation of harmful content. We also replicate the results for two sophisticated types of hate campaigns. While the original findings seem to have been overestimated slightly due
  • @ETN
    Emerging Technologies Papers
    @ETN
    Sep 7
    Automated by @PremiumAccts
    Beyond Maintenance Manual Multimodal RAG: Suggesting What Tool Seongjun Ha, Md Rashedul Islam arxiv.org/abs/2609.05116 [𝚌𝚜.𝙴𝚃 𝚌𝚜.𝙸𝚁]
    Aircraft technicians are required to consult the maintenance manual (MM) for nearly every task, and locating the relevant procedure across hundreds of pages remains time-consuming. Multimodal retrieval augmented generation (MRAG) has been proposed to address this, allowing technicians to retrieve procedures, together with the accompanying figures, through natural-language queries. However, retrieval alone does not tell the technicians which tools the task requires. The MM identifies special tools only when the corresponding step is reached, and it does not state hand tool requirements at all; to select hand tools, technicians are required to find the hardware dimension from the illustrated parts catalog (IPC) and infer the right tool from it. We therefore propose MRAG-SWAT, an extension of the MRAG pipeline that returns the required hand tools and special tools alongside the retrieved procedure. The framework was implemented for the Lycoming IO-360-N1A engine and demonstrated on eight
  • @ETN
    Emerging Technologies Papers
    @ETN
    Sep 7
    Automated by @PremiumAccts
    STEMPix: A Phase-Transition-Material-Based Pixel Sensor for Resolving Edge-Movement Direction Md Rahatul Islam Udoy, Sumeet Kumar Gupta, Deep Jariwala, Ahmedullah Aziz arxiv.org/abs/2609.04435 [𝚌𝚜.𝙴𝚃 𝚌𝚜.𝙲𝚅]
    This paper proposes a spatio-temporal edge-movement direction pixel (STEMPix) for generating compact direction-aware edge movement information inside a CMOS-compatible image sensor array. The proposed design targets specialized sensing applications where local boundary movement is more important than full-frame intensity reconstruction. Instead of transferring full multi-bit frames for external processing, STEMPix generates a 3-bit local edge direction code (LEDC) by combining pixel-level temporal change information with neighboring-pixel spatial edge information. We design the architecture using a two-tier organization, where the photodiode layer is separated from the computation layer to preserve light-collection area while accommodating the additional in-array processing circuitry. The proposed circuit is evaluated through HSPICE transient simulations. The estimated implementation achieves a horizontal pitch of 1.73 μm, a vertical pitch of 2.36 μm, and a geometric fill factor of 95.
  • @ETN
    Emerging Technologies Papers
    @ETN
    Sep 4
    Automated by @PremiumAccts
    QSVT-Based Three-Phase Unbalanced Power Flow Kamini Shahare, Peng Zhang arxiv.org/abs/2609.03165 [𝚌𝚜.𝙴𝚃]
    This letter introduces QSVT-3PF, a quantum singular value transformation (QSVT) based solver for three-phase unbalanced power flow with embedded single-phase grid-forming inverter (GFM) operation. The contributions are threefold: 1) reformulating the Newton correction as a QSVT-compatible inverse problem using a normalized block-encoded phase-domain Jacobian; 2) introducing a regularized singular-value filter to improve robustness under ill-conditioned and stressed operating conditions; and 3) validating the proposed solver on an IEEE 5-bus system and the IEEE 123-node test feeder with single-phase GFM integration. Test results show that QSVT-3PF matches the classical Newton benchmark in residual convergence, voltage profile, and final operating point, demonstrating the feasibility of QSVT-3 for large, unbalanced distribution systems.
  • @ETN
    Emerging Technologies Papers
    @ETN
    Sep 4
    Automated by @PremiumAccts
    Embedding Single-Phase Grid-Forming Inverters in Three-Phase Unbalanced Power Flow Kamini Shahare, Fei Feng, Peng Zhang arxiv.org/abs/2609.03154 [𝚌𝚜.𝙴𝚃]
    This letter introduces Grid-Forming Three-Phase Power Flow (GFM-3PF), an augmented Newton power flow framework for modeling single-phase grid-forming inverters (GFMs) in three-phase unbalanced networks. The contributions of this work are threefold: 1) developing a two-stage solution strategy based on positive-sequence initialization followed by three-phase phase-domain lifting for robust large-scale computation; 2) incorporating phase-domain unbalanced network modeling with controlled mutual coupling together with phase-dependent, frequency-sensitive load representation; and 3) embedding a single-phase GFM bus model directly into the three-phase unbalanced Newton power flow equations through a common droop-governed frequency state. GFM-3PF is validated on 3-bus, 33-bus, and 118-bus test systems, demonstrating its accuracy, robustness, and scalability.
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