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🌉 Aligned Video Captions: Bridging Videos and LLMs for Efficient Retrieval-Augmented Generation

Compact, modality-rich captions for scalable, agentic video understanding in RAG pipelines

Video-Enriched Retrieval Augmented Generation Using Aligned Video Captions [Paper]
Kevin Dela Rosa

Smart Routing for Multimodal Video Retrieval: When to Search What [Paper]
Kevin Dela Rosa

Stay tuned for follow up works using this dataset and future extensions.

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Datasets

Original Aligned Video Captions Dataset

The following are datasets artifacts supporting the 🎞️ Video-Enriched Retrieval Augmented Generation Using Aligned Video Captions publication.

We curated a dataset based on public youtube videos sampled from Panda-70M, which contains individual clip segments and a general visual scene caption learned from a set of open source video captioning models. Specifically we sampled roughly 2,000 videos from each of 15 top level YouTube categories, resulting in a dataset of 29,259 videos (1.5M video clips and corresponding visual captions) or roughly 215 days of footage. We then augmented that dataset with video subtitles gathered from the source videos and created the aligned transcripts.

Statistics for Aligned Video Caption Dataset

DATASET DIMENSION TOTAL MEDIAN
Video Count 29,259 -
Scene Count 1,476,462 31.00
Video Duration (seconds) 18,584,396 478.00
Text Character Length
Title 1,548,810 51.00
Description 30,565,705 780.00
Title + Description 32,114,515 833.00
Visual Video Captions 96,888,187 2,016.00
Subtitles / ASR 141,926,062 3,472.00
Aligned Captions 276,019,918 6,461.00

Dataset Artifacts

Artifact Download
Video Ids link (343KB)
Aligned Video Captions + Limited Metadata link (602MB)
Generated Questions from RAG feasibility Study link (252KB)

If you wish to download the original videos and full video metadata, follow instructions from here. The ChatGPT prompts used for generating video summaries, questions, and automatic judging are provided in prompts folder.

Citation

If you find Aligned Video Captions useful for your research and applications, please cite using this BibTeX:

@inproceedings{10.1145/3701716.3716890,
author = {Dela Rosa, Kevin},
title = {Video-Enriched Retrieval Augmented Generation Using Aligned Video Captions},
year = {2025},
isbn = {9798400713316},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3701716.3716890},
doi = {10.1145/3701716.3716890},
booktitle = {Companion Proceedings of the ACM on Web Conference 2025},
pages = {1663–1667},
numpages = {5},
keywords = {agentic information retrieval, chatbots, multimodal retrieval},
location = {Sydney NSW, Australia},
series = {WWW '25}
}

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