AINeutralarXiv – CS AI · 10h ago6/10
🧠
Spatial Priming Outperforms Semantic Prompting: A Grid-Based Approach to Improving LLM Accuracy on Chart Data Extraction
Researchers demonstrate that overlaying coordinate grids on chart images significantly improves multimodal LLM accuracy for data extraction tasks, reducing error rates from 25.5% to 19.5%. This spatial priming approach outperforms semantic methods like Chain-of-Thought prompting, suggesting that explicit spatial context is more effective than high-level semantic guidance for current-generation vision-language models.