LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917594116653056 |
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| author | Nguyen, Truong Thanh Hung Clement, Tobias Nguyen, Phuc Truong Loc Kemmerzell, Nils Truong, Van Binh Nguyen, Vo Thanh Khang Abdelaal, Mohamed Cao, Hung |
| author_facet | Nguyen, Truong Thanh Hung Clement, Tobias Nguyen, Phuc Truong Loc Kemmerzell, Nils Truong, Van Binh Nguyen, Vo Thanh Khang Abdelaal, Mohamed Cao, Hung |
| contents | LangXAI is a framework that integrates Explainable Artificial Intelligence (XAI) with advanced vision models to generate textual explanations for visual recognition tasks. Despite XAI advancements, an understanding gap persists for end-users with limited domain knowledge in artificial intelligence and computer vision. LangXAI addresses this by furnishing text-based explanations for classification, object detection, and semantic segmentation model outputs to end-users. Preliminary results demonstrate LangXAI's enhanced plausibility, with high BERTScore across tasks, fostering a more transparent and reliable AI framework on vision tasks for end-users. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_12525 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks Nguyen, Truong Thanh Hung Clement, Tobias Nguyen, Phuc Truong Loc Kemmerzell, Nils Truong, Van Binh Nguyen, Vo Thanh Khang Abdelaal, Mohamed Cao, Hung Computer Vision and Pattern Recognition Artificial Intelligence LangXAI is a framework that integrates Explainable Artificial Intelligence (XAI) with advanced vision models to generate textual explanations for visual recognition tasks. Despite XAI advancements, an understanding gap persists for end-users with limited domain knowledge in artificial intelligence and computer vision. LangXAI addresses this by furnishing text-based explanations for classification, object detection, and semantic segmentation model outputs to end-users. Preliminary results demonstrate LangXAI's enhanced plausibility, with high BERTScore across tasks, fostering a more transparent and reliable AI framework on vision tasks for end-users. |
| title | LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2402.12525 |