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KI-Glossar

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Cross-modality

Ability of a system to understand and relate information from different modalities, such as text and images, to enrich contextual understanding.

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Vision-Language Transformer (VLT)

Transformer architecture pre-trained on large corpora of paired images and texts, designed for multimodal comprehension and generation tasks.

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Visual Reasoning

Ability of a QA system to infer non-explicit information by analyzing spatial relationships, object attributes, or complex scenes in an image.

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Visual Grounding

The act of anchoring linguistic concepts (words, phrases) to specific entities or regions in an image or video, creating a tangible semantic link.

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Modality-to-Modality Alignment

Learning process that matches segments of one modality (e.g., a sentence) with relevant segments of another (e.g., an image region).

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Vector Quantized Codebook (VQ)

Technique used in multimodal models to discretize continuous representations (e.g., of images) into a finite set of discrete tokens, facilitating their processing by language models.

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Multimodal Perceptron (MLP)

Neural network, often an MLP, that takes fused features from multiple modalities as input to perform a final classification or regression task.

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Two-Stream Fusion Model

Architecture where each modality is processed by a separate neural network (a stream) before their representations are combined for joint decision-making.

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Multimodal Information Retrieval

Task of retrieving relevant documents (e.g., images) from a query in another modality (e.g., text), based on their similarity in a shared embedding space.

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Conditional Response Generation

Process where a language model generates a textual response whose content is conditioned and guided by information extracted from a non-textual modality such as an image.

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Image Tokenization

Process of converting an image into a sequence of discrete tokens, often via a VAE or VQ-VAE, to make it compatible with Transformer-type architectures.

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