Added: Bottom-Up Abstractive Summarization (sebastianruder#124)

summarization.md

@@ -15,6 +15,7 @@ were trained and evaluated on the anonymized version of the dataset.
 
 | Model           | ROUGE-1 | ROUGE-2 | ROUGE-L | METEOR | Paper / Source | Code |
 | --------------- | :-----: | :-----: | :-----: | :----: | -------------- | ---- |
+| Bottom-Up Summarization (Gehrmann et al., 2018) | 41.22 | 18.68 | 38.34 |  | [Bottom-Up Abstractive Summarization](https://arxiv.org/abs/1808.10792) | [Official](https://github.com/sebastianGehrmann/bottom-up-summary) |
 | Fast-ABS-RL (Chen and Bansal, 2018) | 41.20 | 18.18 | 38.79 | 20.55 | [Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting](https://arxiv.org/abs/1805.11080) | [Official](https://github.com/chenrocks/fast_abs_rl) |
 | DCA (Celikyilmaz et al., 2018) | 41.69| 19.47 | 37.92 | | [Deep Communicating Agents for Abstractive Summarization](https://arxiv.org/abs/1803.10357) | |
 | REFRESH - Extractive model (Narayan et al., 2018) | 40.0 | 18.2 | 36.6 | | [Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://arxiv.org/pdf/1802.08636.pdf) | [Official](https://github.com/EdinburghNLP/Refresh) |