# Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7

arXiv: https://arxiv.org/abs/1806.00525 · HTML: https://mlsanity.com/paper/1806.00525/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jun 2018.

## Built on by (most cited first, 9 of 9)

- [VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs](https://mlsanity.com/paper/2101.12059/) (2021)
- [From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities](https://mlsanity.com/paper/2412.11694/) (2024)
- [MVP: Multi-task Supervised Pre-training for Natural Language Generation](https://mlsanity.com/paper/2206.12131/) (2022)
- [Recent Advances in Video Question Answering: A Review of Datasets and Methods](https://mlsanity.com/paper/2101.05954/) (2021)
- [Can Vision-Language Models Answer Face to Face Questions in the Real-World?](https://mlsanity.com/paper/2503.19356/) (2025)
- [Music Audio-Visual Question Answering Requires Specialized Multimodal Designs](https://mlsanity.com/paper/2505.20638/) (2025)
- [Audio-Visual Intelligence in Large Foundation Models](https://mlsanity.com/paper/2605.04045/) (2026)
- [POVQA: Preference-Optimized Video Question Answering with Rationales for Data Efficiency](https://mlsanity.com/paper/2510.01009/) (2025)
- [From Knowledge Augmentation to Multi-tasking: Towards Human-like Dialogue Systems](https://mlsanity.com/paper/2212.03279/) (2022)

## Abstract (arXiv)

Scene-aware dialog systems will be able to have conversations with users about the objects and events around them. Progress on such systems can be made by integrating state-of-the-art technologies from multiple research areas including end-to-end dialog systems visual dialog, and video description. We introduce the Audio Visual Scene Aware Dialog (AVSD) challenge and dataset. In this challenge, which is one track of the 7th Dialog System Technology Challenges (DSTC7) workshop1, the task is to build a system that generates responses in a dialog about an input video