Despite progress in the field, significant parts of current XAI research are
still not on solid conceptual, ethical, or methodological grounds.
Unfortunately, these unfounded parts are not on the decline but continue to
grow. Many explanation techniques are still proposed without clarifying their
purpose. Instead, they are advertised with ever more fancy-looking heatmaps or
only seemingly relevant benchmarks. Moreover, explanation techniques are
motivated with questionable goals, such as building trust, or rely on strong
assumptions about the 'concepts' that deep learning algorithms learn. In this
paper, we highlight and discuss these and other misconceptions in current XAI
research. We also suggest steps to make XAI a more substantive area of
research.

本文旨在突出和讨论当前 XAI 研究中的概念、伦理或方法论基础不牢的问题及其他误解，同时提出了使 XAI 成为更有实质性研究领域的步骤。

亲爱的 XAI 社区，我们需要谈论！当前 XAI 研究中的根本误解

Dear XAI Community, We Need to Talk! Fundamental Misconceptions in  Current XAI Research

This survey discusses how recent developments in multimodal processing
facilitate conceptual grounding of language. We categorize the information flow
in multimodal processing with respect to cognitive models of human information
processing and analyze different methods for combining multimodal
representations. Based on this methodological inventory, we discuss the benefit
of multimodal grounding for a variety of language processing tasks and the
challenges that arise. We particularly focus on multimodal grounding of verbs
which play a crucial role for the compositional power of language.

本文讨论多模态处理的最新进展，探讨了多模态信息流和不同的多模态表示方法，讨论了多模态基础对于语言处理任务的益处和挑战。特别着重研究动词的多模态基础，对语言的组成能力起着重要作用。