概率性概念解釋器：對於視覺基礎模型的可信概念解釋

Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models

June 18, 2024

作者: Hengyi Wang, Shiwei Tan, Hao Wang

cs.AI

摘要

視覺轉換器（ViTs）已成為一個重要的研究領域，特別是因為它們能夠與大型語言模型聯合訓練，並作為堅固的視覺基礎模型。然而，對於ViTs的可靠解釋方法的發展滯後，特別是在ViT預測的事後解釋方面。現有的子圖像選擇方法，如特徵歸因和概念模型，在這方面表現不佳。本文提出了解釋ViTs的五個期望條件--忠實性、穩定性、稀疏性、多級結構和簡潔性--並展示了目前方法在全面滿足這些標準方面的不足。我們引入了一個變分貝葉斯解釋框架，名為ProbAbilistic Concept Explainers（PACE），它模擬了補丁嵌入的分佈，以提供可信賴的事後概念解釋。我們的定性分析揭示了補丁級概念的分佈，藉此闡明了ViTs的有效性，通過對補丁嵌入和ViT預測的聯合分佈進行建模。此外，這些補丁級解釋填補了圖像級和數據集級解釋之間的差距，從而完成了PACE的多級結構。通過對合成和真實世界數據集的廣泛實驗，我們展示了PACE在所定義的期望條件方面超越了最先進的方法。

English

Vision transformers (ViTs) have emerged as a significant area of focus, particularly for their capacity to be jointly trained with large language models and to serve as robust vision foundation models. Yet, the development of trustworthy explanation methods for ViTs has lagged, particularly in the context of post-hoc interpretations of ViT predictions. Existing sub-image selection approaches, such as feature-attribution and conceptual models, fall short in this regard. This paper proposes five desiderata for explaining ViTs -- faithfulness, stability, sparsity, multi-level structure, and parsimony -- and demonstrates the inadequacy of current methods in meeting these criteria comprehensively. We introduce a variational Bayesian explanation framework, dubbed ProbAbilistic Concept Explainers (PACE), which models the distributions of patch embeddings to provide trustworthy post-hoc conceptual explanations. Our qualitative analysis reveals the distributions of patch-level concepts, elucidating the effectiveness of ViTs by modeling the joint distribution of patch embeddings and ViT's predictions. Moreover, these patch-level explanations bridge the gap between image-level and dataset-level explanations, thus completing the multi-level structure of PACE. Through extensive experiments on both synthetic and real-world datasets, we demonstrate that PACE surpasses state-of-the-art methods in terms of the defined desiderata.