Discrete and continuous representations and processing in deep learning: Looking forward

4 January 2022

Papers citing "Discrete and continuous representations and processing in deep learning: Looking forward"

7 / 7 papers shown

Title
Towards Equipping Transformer with the Ability of Systematic Compositionality Chen Huang Peixin Qin Wenqiang Lei Jiancheng Lv 19 1 0 12 Dec 2023
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review Kyle Hamilton Aparna Nayak Bojan Bozic Luca Longo NAI 21 57 0 24 Feb 2022
Do Transformers know symbolic rules, and would we know if they did? Tommi Gröndahl Yu-Wen Guo Nirmal Asokan 17 0 0 19 Feb 2022
Neural Enhanced Belief Propagation on Factor Graphs Victor Garcia Satorras Max Welling 22 94 0 04 Mar 2020
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 199 882 0 03 May 2018
Image Generation from Scene Graphs Justin Johnson Agrim Gupta Li Fei-Fei GNN 221 815 0 04 Apr 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,244 0 16 Jan 2013