AI RESEARCH
Unlocking the Latent Canvas: Eliciting and Benchmarking Symbolic Visual Expression in LLMs
arXiv CS.CV
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ArXi:2603.14505v1 Announce Type: new Current multimodal approaches predominantly treat visual generation as an external process, relying on pixel rendering or code execution, thereby overlooking the native visual representation capabilities latent within Large Language Models (LLMs). In this work, we unlock this potential through ASCII art, a compact, efficient, and text-native visual format. We