本人关于鲁棒音视频问答的论文被NeurIPS 2024接收
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发布时间：2024-09-26
发布时间：2024-09-26
文章标题：本人关于鲁棒音视频问答的论文被NeurIPS 2024接收
内容：
- 会议介绍：NeurIPS，全称神经信息处理系统大会，是一个关于机器学习和计算神经科学的国际会议。该会议固定在每年的12月举行,由NIPS基金会主办。NIPS是机器学习领域的顶级会议 。在中国计算机学会、中国人工智能学会的国际学术会议排名中，NeurIPS为人工智能领域的A类会议。
- 论文题目：Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
- 论文摘要：Audio-Visual Question Answering (AVQA) is a complex multi-modal reasoning task, demanding intelligent systems to accurately respond to natural language queries based on audio-video input pairs. Nevertheless, prevalent AVQA approaches are prone to overlearning dataset biases, resulting in poor robustness. Furthermore, current datasets may not provide a precise diagnostic for these methods. To tackle these challenges, firstly, we propose a novel dataset, \textit{MUSIC-AVQA-R}, crafted in two steps: rephrasing questions within the test split of a public dataset (\textit{MUSIC-AVQA}) and subsequently introducing distribution shifts to split questions. The former leads to a large, diverse test space, while the latter results in a comprehensive robustness evaluation on rare, frequent, and overall questions. Secondly, we propose a robust architecture that utilizes a multifaceted cycle collaborative debiasing strategy to overcome bias learning. Experimental results show that this architecture achieves state-of-the-art performance on both datasets, especially obtaining a significant improvement of 9.32\% on the proposed dataset. Extensive ablation experiments are conducted on these two datasets to validate the effectiveness of the debiasing strategy. Additionally, we highlight the limited robustness of existing multi-modal QA methods through the evaluation on our dataset.
- 论文代码：https://github.com/reml-group/MUSIC-AVQA-R.