The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
Tianyang Han, Qing Lian, Rui Pan, Renjie Pi, Jipeng Zhang, Shizhe Diao, Yong Lin, Tong Zhang
Abstract
Large language models (LLMs) have recently experienced remarkable progress, where the advent of multi-modal large language models (MLLMs) has endowed LLMs with visual capabilities, leading to impressive performances in various multi-modal tasks. However, those powerful MLLMs such as GPT-4V still fail spectacularly when presented with certain image and text inputs. In this paper, we identify a typical class of inputs that baffles MLLMs, which consist of images that are highly relevant but inconsistent with answers, causing MLLMs to suffer from visual illusion. To quantify the effect, we propose CorrelationQA, the first benchmark that assesses the visual illusion level given spurious images. This benchmark contains 7,308 text-image pairs across 13 categories. Based on the proposed CorrelationQA, we conduct a thorough analysis on 9 mainstream MLLMs, illustrating that they universally suffer from this instinctive bias to varying degrees. We hope that our curated benchmark and evaluation results aid in better assessments of the MLLMs’ robustness in the presence of misleading images. The code and datasets are available at https://github.com/MasaiahHan/CorrelationQA.- Anthology ID:
- 2024.emnlp-main.904
- Volume:
- Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 16163–16177
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.emnlp-main.904/
- DOI:
- 10.18653/v1/2024.emnlp-main.904
- Cite (ACL):
- Tianyang Han, Qing Lian, Rui Pan, Renjie Pi, Jipeng Zhang, Shizhe Diao, Yong Lin, and Tong Zhang. 2024. The Instinctive Bias: Spurious Images lead to Illusion in MLLMs. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 16163–16177, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- The Instinctive Bias: Spurious Images lead to Illusion in MLLMs (Han et al., EMNLP 2024)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.emnlp-main.904.pdf