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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2510.06782 |
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| _version_ | 1866909831072317440 |
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| author | Yang, Kaichun Chen, Jian |
| author_facet | Yang, Kaichun Chen, Jian |
| contents | We present a quantitative evaluation to understand the effect of zero-shot large-language model (LLMs) and prompting uses on chart reading tasks. We asked LLMs to answer 107 visualization questions to compare inference accuracies between the agentic GPT-5 and multimodal GPT-4V, for difficult image instances, where GPT-4V failed to produce correct answers. Our results show that model architecture dominates the inference accuracy: GPT5 largely improved accuracy, while prompt variants yielded only small effects. Pre-registration of this work is available here: https://osf.io/u78td/?view_only=6b075584311f48e991c39335c840ded3; the Google Drive materials are here:https://drive.google.com/file/d/1ll8WWZDf7cCNcfNWrLViWt8GwDNSvVrp/view. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06782 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GPT-5 Model Corrected GPT-4V's Chart Reading Errors, Not Prompting Yang, Kaichun Chen, Jian Human-Computer Interaction Computation and Language Computer Vision and Pattern Recognition We present a quantitative evaluation to understand the effect of zero-shot large-language model (LLMs) and prompting uses on chart reading tasks. We asked LLMs to answer 107 visualization questions to compare inference accuracies between the agentic GPT-5 and multimodal GPT-4V, for difficult image instances, where GPT-4V failed to produce correct answers. Our results show that model architecture dominates the inference accuracy: GPT5 largely improved accuracy, while prompt variants yielded only small effects. Pre-registration of this work is available here: https://osf.io/u78td/?view_only=6b075584311f48e991c39335c840ded3; the Google Drive materials are here:https://drive.google.com/file/d/1ll8WWZDf7cCNcfNWrLViWt8GwDNSvVrp/view. |
| title | GPT-5 Model Corrected GPT-4V's Chart Reading Errors, Not Prompting |
| topic | Human-Computer Interaction Computation and Language Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2510.06782 |