# Reactive Multi-Stage Feature Fusion for Multimodal Dialogue Modeling

arXiv: https://arxiv.org/abs/1908.05067 · HTML: https://mlsanity.com/paper/1908.05067/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Aug 2019.

## Built on by (most cited first, 4 of 4)

- [Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue](https://mlsanity.com/paper/2212.05765/) (2022)
- [Structured Co-reference Graph Attention for Video-grounded Dialogue](https://mlsanity.com/paper/2103.13361/) (2021)
- [Video Dialog as Conversation about Objects Living in Space-Time](https://mlsanity.com/paper/2207.03656/) (2022)
- [Uncovering Hidden Connections: Iterative Search and Reasoning for Video-grounded Dialog](https://mlsanity.com/paper/2310.07259/) (2023)

## Abstract (arXiv)

Visual question answering and visual dialogue tasks have been increasingly studied in the multimodal field towards more practical real-world scenarios. A more challenging task, audio visual scene-aware dialogue (AVSD), is proposed to further advance the technologies that connect audio, vision, and language, which introduces temporal video information and dialogue interactions between a questioner and an answerer. This paper proposes an intuitive mechanism that fuses features and attention in multiple stages in order to well integrate multimodal features, and the results demonstrate its capability in the experiments. Also, we apply several state-of-the-art models in other tasks to the AVSD task, and further analyze their generalization across different tasks.