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  • GitHub - OpenGVLab LAMM: [NeurIPS 2023 Datasets and . . .
    LAMM (pronounced as læm , means cute lamb to show appreciation to LLaMA), is a growing open-source community aimed at helping researchers and developers quickly train and evaluate Multi-modal Large Language Models (MLLM), and further build multi-modal AI agents capable of bridging the gap between ideas and execution, enabling seamless
  • Home - Lamm Food Service
    From restaurants to convenience stores, drive-ins, mobile caterers, nursing homes, distributors, schools and correctional facilities and more – customers throughout Louisiana and beyond have been relying upon LAMM Food Service for the best products and unsurpassed service since 1972
  • Quite simply, the world’s best audio electronics | LAMM
    Setting the standard for audiophiles the world over, LAMM Industries designs state-of-the-art audio products that deliver breakthrough performance with uncompromised sonic quality
  • [2306. 06687] LAMM: Language-Assisted Multi-Modal Instruction . . .
    Large language models have emerged as a promising approach towards achieving general-purpose AI agents The thriving open-source LLM community has greatly accelerated the development of agents that support human-machine dialogue interaction through natural language processing
  • About LAMM | LAMM
    Today, nearly three decades later, the family-led enterprise of sonic excellence continues—with a legacy of award-winning equipment heralded as the reference standard for audiophiles around the world— from our LL2 1 linestage preamplifier to the ML3 Signature monoblock amplifier
  • Corporate - LAMM
    Since 1959, LAMM has produced and installed throughout the world seating systems for conference rooms, auditoriums, universities, cinemas, theatres and community facilities
  • LAMM: Label Alignment for Multi-Modal Prompt Learning [AAAI 2024]
    To address this challenge, we introduce an innovative label alignment method named \textbf {LAMM}, which can dynamically adjust the category embeddings of downstream datasets through end-to-end training





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