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    MGIE

    MGIE

    Guiding Instruction-based Image Editing via Multimodal Large Language

    ...The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations. This bridges a gap between free-form prompts and precise edits by letting users describe “what” and “where” in everyday language. The repo includes instructions, examples, and links that situate MGIE within Apple’s broader line of multimodal research. For practitioners, MGIE provides a blueprint for text-to-edit systems that are more semantically grounded than naive prompt-only pipelines.
    Downloads: 0 This Week
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    Controllable-RAG-Agent

    Controllable-RAG-Agent

    This repository provides an advanced RAG

    ...The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. A key focus is hallucination control: each answer is verified against retrieved context, and responses are reworked when they are not sufficiently grounded in the source documents.
    Downloads: 0 This Week
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