[2024 Best AI Paper] ReMamba: Equip Mamba with Effective Long-Sequence Modeling

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This video was created using https://paperspeech.com. If you’d like to create explainer videos for your own papers, please visit the website! Title: ReMamba: Equip Mamba with Effective Long-Sequence Modeling Authors: Danlong Yuan, Jiahao Liu, Bei Li, Huishuai Zhang, Jingang Wang, Xunliang Cai, Dongyan Zhao Abstract: While the Mamba architecture demonstrates superior inference efficiency and competitive performance on short-context natural language processing (NLP) tasks, empirical evidence suggests its capacity to comprehend long contexts is limited compared to transformer-based models. In this study, we investigate the long-context efficiency issues of the Mamba models and propose ReMamba, which enhances Mamba's ability to comprehend long contexts. ReMamba incorporates selective compression and adaptation techniques within a two-stage re-forward process, incurring minimal additional inference costs overhead. Experimental results on the LongBench and L-Eval benchmarks demonstrate Re