Compositionality decomposed: how do neural networks generalise?

22 August 2019

Verna Dankers

Papers citing "Compositionality decomposed: how do neural networks generalise?"

21 / 71 papers shown

Title
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN R. Thomas McCoy P. Smolensky Tal Linzen Jianfeng Gao Asli Celikyilmaz SyDa 17 119 0 18 Nov 2021
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks Wang Zhu Peter Shaw Tal Linzen Fei Sha 27 7 0 09 Nov 2021
The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization Róbert Csordás Kazuki Irie Jürgen Schmidhuber AI4CE 25 55 0 14 Oct 2021
Survey of Low-Resource Machine Translation Barry Haddow Rachel Bawden Antonio Valerio Miceli Barone Jindvrich Helcl Alexandra Birch AIMat 31 147 0 01 Sep 2021
The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers Róbert Csordás Kazuki Irie Jürgen Schmidhuber ViT 23 128 0 26 Aug 2021
Making Transformers Solve Compositional Tasks Santiago Ontañón Joshua Ainslie Vaclav Cvicek Zachary Kenneth Fisher 33 70 0 09 Aug 2021
Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN Rahma Chaabouni Roberto Dessì Eugene Kharitonov 19 20 0 03 Jul 2021
Improving Compositional Generalization in Classification Tasks via Structure Annotations Juyong Kim Pradeep Ravikumar Joshua Ainslie Santiago Ontañón CoGe 16 18 0 19 Jun 2021
Grounding Spatio-Temporal Language with Transformers Tristan Karch Laetitia Teodorescu Katja Hofmann Clément Moulin-Frier Pierre-Yves Oudeyer LM&Ro 14 11 0 16 Jun 2021
Disentangling Syntax and Semantics in the Brain with Deep Networks Charlotte Caucheteux Alexandre Gramfort J. King 34 69 0 02 Mar 2021
Probing Multimodal Embeddings for Linguistic Properties: the Visual-Semantic Case Adam Dahlgren Lindström Suna Bensch Johanna Björklund F. Drewes 16 20 0 22 Feb 2021
Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization Yinuo Guo Hualei Zhu Zeqi Lin Bei Chen Jian-Guang Lou Dongmei Zhang BDL 182 26 0 08 Dec 2020
Scaling Laws for Autoregressive Generative Modeling T. Henighan Jared Kaplan Mor Katz Mark Chen Christopher Hesse ... Nick Ryder Daniel M. Ziegler John Schulman Dario Amodei Sam McCandlish 25 405 0 28 Oct 2020
Neural Databases James Thorne Majid Yazdani Marzieh Saeidi Fabrizio Silvestri Sebastian Riedel A. Halevy NAI 26 9 0 14 Oct 2020
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks Róbert Csordás Sjoerd van Steenkiste Jürgen Schmidhuber 23 87 0 05 Oct 2020
Systematic Generalization on gSCAN with Language Conditioned Embedding Tong Gao Qi Huang Raymond J. Mooney 16 22 0 11 Sep 2020
Compositional Generalization by Learning Analytical Expressions Qian Liu Shengnan An Jian-Guang Lou Bei Chen Zeqi Lin Yan Gao Bin Zhou Nanning Zheng Dongmei Zhang CoGe NAI 13 72 0 18 Jun 2020
A Study of Compositional Generalization in Neural Models Tim Klinger D. Adjodah Vincent Marois Joshua Joseph Matthew D Riemer Alex Pentland Murray Campbell CoGe NAI 15 12 0 16 Jun 2020
Discovering the Compositional Structure of Vector Representations with Role Learning Networks Paul Soulos R. Thomas McCoy Tal Linzen P. Smolensky CoGe 29 43 0 21 Oct 2019
OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein Yoon Kim Yuntian Deng Jean Senellart Alexander M. Rush 256 1,896 0 10 Jan 2017
From Frequency to Meaning: Vector Space Models of Semantics Peter D. Turney Patrick Pantel 82 2,980 0 04 Mar 2010