2501.05874
arxiv.org · 6,170 words · saved by 1 readers
N/A
VideoRAG: Retrieval-Augmented Generation over Video Corpus Soyeong Jeong1∗ Kangsan Kim1∗ Jinheon Baek1∗ Sung Ju Hwang1,2 KAIST1 DeepAuto.ai2 {starsuzi, kksan07, jinheon.baek, sungju.hwang}@kaist.ac.kr Abstract (A) Textual RAG…
saved by
related reading
- 2025.acl-long.842.pdfaclanthology.org
- [2005.11401] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasksarxiv.org
- Video models are zero-shot learners and reasonersarxiv.org
- [2506.09985] V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planningarxiv.org
- Retrieval-Augmented Generation for Large Language Models: A Surveyarxiv.org
- 2025.acl-long.896.pdfaclanthology.org
- Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing modelsai.facebook.com
- 2502.11089arxiv.org
- Video Generation Models Explosion 2024yenchenlin.me
- Code a simple RAG from scratchhuggingface.co
- 45d74e190008c7bff2845ffc8e3facd3-Paper-Conference.pdfproceedings.iclr.cc
- 2025.findings-emnlp.313.pdfaclanthology.org