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A Continuous Relaxation of Beam Search for End-to-end Training of Neural
  Sequence Models
v1v2 (latest)

A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models

1 August 2017
Kartik Goyal
Graham Neubig
Chris Dyer
Taylor Berg-Kirkpatrick
    3DV
ArXiv (abs)PDFHTML

Papers citing "A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models"

26 / 26 papers shown
Title
Beam Tree Recursive Cells
Beam Tree Recursive Cells
Jishnu Ray Chowdhury
Cornelia Caragea
91
6
0
31 May 2023
Learning to Summarize Videos by Contrasting Clips
Learning to Summarize Videos by Contrasting Clips
Ivan Sosnovik
A. Moskalev
Cees Kaandorp
A. Smeulders
66
0
0
12 Jan 2023
Differentiable Top-k Classification Learning
Differentiable Top-k Classification Learning
Felix Petersen
Hilde Kuehne
Christian Borgelt
Oliver Deussen
135
32
0
15 Jun 2022
Monotonic Differentiable Sorting Networks
Monotonic Differentiable Sorting Networks
Felix Petersen
Christian Borgelt
Hilde Kuehne
Oliver Deussen
73
26
0
17 Mar 2022
Learning Energy-Based Approximate Inference Networks for Structured
  Applications in NLP
Learning Energy-Based Approximate Inference Networks for Structured Applications in NLP
Lifu Tu
BDL
64
0
0
27 Aug 2021
Incremental Beam Manipulation for Natural Language Generation
Incremental Beam Manipulation for Natural Language Generation
J. Hargreaves
Andreas Vlachos
Guy Edward Toh Emerson
48
7
0
04 Feb 2021
An Empirical Investigation of Beam-Aware Training in Supertagging
An Empirical Investigation of Beam-Aware Training in Supertagging
Renato M. P. Negrinho
Matthew R. Gormley
Geoffrey J. Gordon
83
3
0
10 Oct 2020
Successive Halving Top-k Operator
Successive Halving Top-k Operator
Michal Pietruszka
Łukasz Borchmann
Filip Graliñski
38
6
0
08 Oct 2020
Text Generation by Learning from Demonstrations
Text Generation by Learning from Demonstrations
Richard Yuanzhe Pang
He He
OffRL
70
80
0
16 Sep 2020
Sparsifying Transformer Models with Trainable Representation Pooling
Sparsifying Transformer Models with Trainable Representation Pooling
Michal Pietruszka
Łukasz Borchmann
Lukasz Garncarek
91
12
0
10 Sep 2020
Learning Optimal Tree Models Under Beam Search
Learning Optimal Tree Models Under Beam Search
Jingwei Zhuo
Xinhang Li
Wei Dai
Ziru Xu
Han Li
Jian Xu
Kun Gai
79
60
0
27 Jun 2020
Natural Language Processing Advancements By Deep Learning: A Survey
Natural Language Processing Advancements By Deep Learning: A Survey
A. Torfi
Rouzbeh A. Shirvani
Yaser Keneshloo
Nader Tavvaf
Edward A. Fox
AI4CEVLM
161
222
0
02 Mar 2020
Differentiable Top-k Operator with Optimal Transport
Differentiable Top-k Operator with Optimal Transport
Yujia Xie
H. Dai
Minshuo Chen
Bo Dai
T. Zhao
H. Zha
Wei Wei
Tomas Pfister
OT
70
27
0
16 Feb 2020
Neural Machine Translation: A Review and Survey
Neural Machine Translation: A Review and Survey
Felix Stahlberg
3DVAI4TSMedIm
142
332
0
04 Dec 2019
Deep Learning Based Chatbot Models
Deep Learning Based Chatbot Models
Richard Csaky
74
46
0
23 Aug 2019
An Empirical Investigation of Global and Local Normalization for
  Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search
An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search
Kartik Goyal
Chris Dyer
Taylor Berg-Kirkpatrick
63
16
0
15 Apr 2019
Benchmarking Approximate Inference Methods for Neural Structured
  Prediction
Benchmarking Approximate Inference Methods for Neural Structured Prediction
Lifu Tu
Kevin Gimpel
BDL
93
17
0
01 Apr 2019
Stochastic Optimization of Sorting Networks via Continuous Relaxations
Stochastic Optimization of Sorting Networks via Continuous Relaxations
Aditya Grover
Eric Wang
Aaron Zweig
Stefano Ermon
101
174
0
21 Mar 2019
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for
  Sampling Sequences Without Replacement
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
W. Kool
H. V. Hoof
Max Welling
142
220
0
14 Mar 2019
A Fully Differentiable Beam Search Decoder
A Fully Differentiable Beam Search Decoder
R. Collobert
Awni Y. Hannun
Gabriel Synnaeve
86
40
0
16 Feb 2019
Value-based Search in Execution Space for Mapping Instructions to
  Programs
Value-based Search in Execution Space for Mapping Instructions to Programs
Dor Muhlgay
Jonathan Herzig
Jonathan Berant
63
6
0
02 Nov 2018
Learning Beam Search Policies via Imitation Learning
Learning Beam Search Policies via Imitation Learning
Renato M. P. Negrinho
Matthew R. Gormley
Geoffrey J. Gordon
118
27
0
01 Nov 2018
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a
  Structured Variational Autoencoder
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder
Caio Corro
Ivan Titov
BDL
58
56
0
25 Jul 2018
Learning Approximate Inference Networks for Structured Prediction
Learning Approximate Inference Networks for Structured Prediction
Lifu Tu
Kevin Gimpel
BDL
59
53
0
09 Mar 2018
Differentiable Dynamic Programming for Structured Prediction and
  Attention
Differentiable Dynamic Programming for Structured Prediction and Attention
A. Mensch
Mathieu Blondel
75
131
0
11 Feb 2018
Differentiable lower bound for expected BLEU score
Differentiable lower bound for expected BLEU score
Vlad Zhukov
Eugene Golikov
M. Kretov
43
15
0
13 Dec 2017
1