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  • QuickSRNet: Plain Single-Image Super-Resolution Architecture . . .
    Abstract In this work, we present QuickSRNet, an eficient super-resolution architecture for real-time applications on mobile platforms Super-resolution clarifies, sharpens, and up-scales an image to higher resolution Applications such as gaming and video playback along with the ever-improving display capabilities of TVs, smartphones, and VR headsets are driving the need for eficient
  • (version 1) - export. arxiv. org
    Notable insights include: • The GPT-2 architecture, with rotary embedding, matches or even surpasses LLaMA Mistral architectures in knowledge storage, particularly over shorter training durations This arises because LLaMA Mistral uses GatedMLP, which is less stable and harder to train
  • AiReview: An Open Platform for Accelerating Systematic . . .
    2 TITLE AND ABSTRACT SCREENING WITH AIREVIEW An overview of AiReview’s architecture is shown in Figure 1 At nbib high-level, users upload studies retrieved from PubMed in format, along with the corresponding inclusion criteria for the SR as the input for LLM-assisted screening After the screening, users can download the screened studies
  • CONVERSATIONAL AI: REDEFINING HUMAN EXPERIENCE - Dell
    The reference architecture in Figure 7 depicts how to build an enterprise-grade conversational bot using the Azure Bot Framework, to serve enterprise-grade workloads
  • (version 1) - web3. arxiv. org
    Notable insights include: • The GPT-2 architecture, with rotary embedding, matches or even surpasses LLaMA Mistral architectures in knowledge storage, particularly over shorter training durations This arises because LLaMA Mistral uses GatedMLP, which is less stable and harder to train
  • LoMA: Lossless Compressed Memory Attention - arXiv. org
    Abstract Large Language Models (LLMs) face limitations due to the high demand on GPU memory and computational resources when handling long con-texts While sparsify the Key-Value (KV) cache of transformer model is a typical strategy to al-leviate resource usage, it unavoidably results in the loss of information We introduce Lossless Compressed Memory Attention (LoMA), a novel approach that
  • VWHP - stats. iop. org
    Three main pixel architectures, the ALPIDE architecture and the ASTRAL MISTRAL archi- tectures, are under study for the use in the upgraded ALICE ITS, with the goal to select a common design in the first half of 2015


















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