VisGym Exposed: Why GPT-5 & Gemini 2.5 Pro Fail at Simple Visual Puzzles
1 months ago 高效码农VisGym: The Ultimate Test for Vision-Language Models – Why Top AI Agents Struggle with Multi-Step Tasks The Core Question Answered Here: While Vision-Language Models (VLMs) excel at static image recognition, can they truly succeed in environments requiring perception, memory, and action over long periods? Why do the most advanced “frontier” models frequently fail at seemingly simple multi-step visual tasks? In the rapidly evolving landscape of artificial intelligence, Vision-Language Models have become the bridge connecting computer vision with natural language processing. From identifying objects in a photo to answering complex questions about an image, their performance is often nothing short of …
nanoVLM: The Ultimate Guide to Training Vision-Language Models in PyTorch
9 months ago 高效码农nanoVLM: The Simplest Guide to Training Vision-Language Models in Pure PyTorch What Is a Vision-Language Model (VLM)? What Can It Do? Imagine showing a computer a photo of cats and asking, “How many cats are in this image?” The computer not only understands the image but also answers your question in text. This type of model—capable of processing both visual and textual inputs to generate text outputs—is called a Vision-Language Model (VLM). In nanoVLM, we focus on Visual Question Answering (VQA). Below are common applications of VLMs: Input Type Example Question Example Output Task Type “Describe this image” “Two cats …