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  • IMMA

    IMMA is a memory-augmented AI agent enabling long-term, multi-modal context retrieval for personalized conversational assistance.
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    What is IMMA?
    IMMA (Interactive Multi-Modal Memory Agent) is a modular framework designed to enhance conversational AI with persistent memory. It encodes text, image, and other data from past interactions into an efficient memory store, performs semantic retrieval to provide relevant context during new dialogues, and applies summarization and filtering techniques to maintain coherence. IMMA’s APIs enable developers to define custom memory insertion and retrieval policies, integrate multi-modal embeddings, and fine-tune the agent for domain-specific tasks. By managing long-term user context, IMMA supports use cases that require continuity, personalization, and multi-turn reasoning over extended sessions.
    IMMA Core Features
    • Long-term multi-modal memory encoding
    • Semantic memory retrieval
    • Memory summarization and filtering
    • Context-aware multi-turn dialogues
    • Customizable memory policies and storage
    IMMA Pro & Cons

    The Cons

    The Pros

    Models multiple independent interaction types simultaneously via multiplex latent graphs.
    Uses attention mechanisms to weigh relation strengths enhancing model expressiveness.
    Progressive Layer Training improves learning of layered interactions and forecasting accuracy.
    Better long-term trajectory prediction compared to prior methods.
    Improved interpretability of multi-agent social interactions.
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