Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN

3 July 2021

Papers citing "Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN"

9 / 9 papers shown

Title
Layer-wise Representation Fusion for Compositional Generalization Yafang Zheng Lei Lin Shantao Liu Binling Wang Zhaohong Lai Wenhao Rao Biao Fu Yidong Chen Xiaodon Shi AI4CE 43 2 0 20 Jul 2023
Learning to Compose Representations of Different Encoder Layers towards Improving Compositional Generalization Lei Lin Shuangtao Li Yafang Zheng Biao Fu Shantao Liu Yidong Chen Xiaodon Shi CoGe 25 2 0 20 May 2023
Categorizing Semantic Representations for Neural Machine Translation Yongjing Yin Yafu Li Fandong Meng Jie Zhou Yue Zhang 24 6 0 13 Oct 2022
State-of-the-art generalisation research in NLP: A taxonomy and review Dieuwke Hupkes Mario Giulianelli Verna Dankers Mikel Artetxe Yanai Elazar ... Leila Khalatbari Maria Ryskina Rita Frieske Ryan Cotterell Zhijing Jin 114 93 0 06 Oct 2022
Improving Systematic Generalization Through Modularity and Augmentation Laura Ruis Brenden Lake 43 16 0 22 Feb 2022
Towards Interactive Language Modeling Maartje ter Hoeve Evgeny Kharitonov Dieuwke Hupkes Emmanuel Dupoux 26 4 0 14 Dec 2021
The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization Róbert Csordás Kazuki Irie Jürgen Schmidhuber AI4CE 33 55 0 14 Oct 2021
Sequence-to-Sequence Learning with Latent Neural Grammars Yoon Kim 33 40 0 02 Sep 2021
The paradox of the compositionality of natural language: a neural machine translation case study Verna Dankers Elia Bruni Dieuwke Hupkes CoGe 162 75 0 12 Aug 2021