vlm
FDE interview questions tagged vlm, across every topic.
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Concepts behind "vlm"
The curriculum that explains the ideas these questions test.
Core
Multimodal Models and VLMsA vision-language model lets an LLM see by running images through a vision encoder and a projection layer that turns them into tokens the language model reads alongside text. CLIP-style contrastive training aligns image and text into one embedding space, powering image search and zero-shot classification. FDE loops probe this because document, chart, and screenshot understanding is a common deployment, and the failure modes (counting, fine detail, hallucinated visual facts) are specific.🧠 Foundations of LLMs & GenAISign in
Advanced
Document Parsing and ExtractionGetting typed fields out of PDFs, scans and forms is the first stage of most enterprise AI pipelines and the one most pilots never test. Extraction is a ladder (text layer, OCR, layout model, vision model) chosen per page, its output is a schema with a confidence and a location per field, and its accuracy compounds: if field errors were independent, 96% per field would be 61% of twelve-field documents fully correct. The decisions that matter are which rung each page gets, and which fields a human still checks.🤖 Retrieval & Agents🔒 Premium