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%0 Conference Proceedings%T A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization%A Wang, William Yang%A Mehdad, Yashar%A Radev, Dragomir R.%A Stent, Amanda%Y Knight, Kevin%Y Nenkova, Ani%Y Rambow, Owen%S Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies%D 2016%8 June%I Association for Computational Linguistics%C San Diego, California%F wang-etal-2016-low%R 10.18653/v1/N16-1008%U https://aclanthology.org/N16-1008/%U https://doi.org/10.18653/v1/N16-1008%P 58-68

Markdown (Informal)

[A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization](https://aclanthology.org/N16-1008/) (Wang et al., NAACL 2016)

• A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization (Wang et al., NAACL 2016)

ACL

• William Yang Wang, Yashar Mehdad, Dragomir R. Radev, and Amanda Stent. 2016.A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization. InProceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 58–68, San Diego, California. Association for Computational Linguistics.