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Showing 1 to 4 of 4 for “"LLM deployment"”.

  1. Augmenting large language models with static code analysis for accelerated software development and quality improvements

    … pipeline driven by large language models (LLMs) to accelerate the quality assurance (QA) phase of the software development lifecycle using static analysis tools. NGQA integrates detection, grounding, revision, validation, and coordination into a unified workflow through a verification-aware …

    uoit Repository record for Augmenting large language models with static code analysis for accelerated software development and quality improvements (opens in a new tab)

  2. On the Resource Efficiency of Language Models

    Large language models (LLMs) have revolutionized a wide range of natural language processing tasks. However, their practical utility faces resource challenges in two dimensions: data efficiency and model efficiency. For post-training, LLMs face data curation challenges where high-quality labeled …

    gatech Repository record for On the Resource Efficiency of Language Models (opens in a new tab)

  3. Co-Designing Efficient Systems and Algorithms for Sparse and Quantized Deep Learning Computing

    … models, necessitating quantization for efficient deployment. This thesis presents two GPU systems for accelerating large language models (LLMs): TinyChat for edge LLM deployment and QServe for cloud-based LLM serving. TinyChat boosts edge LLM inference by 3× using activation-aware weight …

    mit Repository record for Co-Designing Efficient Systems and Algorithms for Sparse and Quantized Deep Learning Computing (opens in a new tab)

  4. Trustworthy Federated Learning Systems: From Secure Distributed Training to Reliable Fine-tuning

    … widespread adoption of Large Language Models (LLMs) has expanded the threat landscape well beyond the training phase. Because LLMs process unpredictable user inputs and unverified external content, they are susceptible to novel inference-time vulnerabilities. These include jailbreaking and …

    exeter