Abstract
In the months since its release, ChatGPT and its underlying model, GPT3.5, have garnered massive attention, due to their potent mix of capability and accessibility. While a niche industry of papers have emerged examining the scope of capabilities these models possess, language — whether natural or stylized like code — has been the vehicle to exchange information with the network. Drawing inspiration from the multi-modal knowledge we’d expect an agent with true understanding to possess, we examine GPT3.5’s aptitude for visual tasks, where the inputs feature ASCII-art without overt distillation into a lingual summary. In particular, we scrutinize its performance on carefully designed image recognition and generation tasks. An extended version of this write-up is available at: https://arxiv.org/abs/2307.16806 .- Anthology ID:
- 2024.findings-eacl.139
- Volume:
- Findings of the Association for Computational Linguistics: EACL 2024
- Month:
- March
- Year:
- 2024
- Address:
- St. Julian’s, Malta
- Editors:
- Yvette Graham, Matthew Purver
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2063–2077
- Language:
- URL:
- https://aclanthology.org/2024.findings-eacl.139
- DOI:
- Cite (ACL):
- David Bayani. 2024. Testing the Depth of ChatGPT’s Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3.5’s Abilities in Regard to Recognizing and Generating ASCII-Art Are Not Totally Lacking. In Findings of the Association for Computational Linguistics: EACL 2024, pages 2063–2077, St. Julian’s, Malta. Association for Computational Linguistics.
- Cite (Informal):
- Testing the Depth of ChatGPT’s Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3.5’s Abilities in Regard to Recognizing and Generating ASCII-Art Are Not Totally Lacking (Bayani, Findings 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.findings-eacl.139.pdf