Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models

Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules

Weininger, D · 1988

Earlier work this paper cites.

Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks

Graves, A., Fernández, S., Gomez, F., and Schmidhuber, J · 2006

Earlier work this paper cites.

Task loss estimation for sequence prediction

Original

Bahdanau, D., Serdyuk, D., Brakel, P., Ke, N. R., Chorowski, J., Courville, A., and Bengio, Y · 2015

Earlier work this paper cites.

Deep unsupervised learning using nonequilibrium thermodynamics

Original

Sohl-Dickstein, J., Weiss, E. A., Maheswaranathan, N., and Ganguli, S · 2015

Earlier work this paper cites.

WaveNet: A generative model for raw audio

Original

van den Oord, A., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., and Kavukcuoglu, K · 2016

Earlier work this paper cites.

Learning how to simplify from explicit labeling of complex-simplified text pairs

Alva-Manchego, F., Bingel, J., Paetzold, G., Scarton, C., and Specia, L · 2017

Earlier work this paper cites.

Generating sentences by editing prototypes

Guu, K., Hashimoto, T. B., Oren, Y., and Liang, P · 2018

Earlier work this paper cites.

Optimal completion distillation for sequence learning

Original

Sabour, S., Chan, W., and Norouzi, M · 2018

Earlier work this paper cites.

EditNTS: An neural programmer-interpreter model for sentence simplification through explicit editing

Dong, Y., Li, Z., Rezagholizadeh, M., and Cheung, J. C. K · 2019

Earlier work this paper cites.

Mask-Predict: Parallel decoding of conditional masked language models

Original

Ghazvininejad, M., Levy, O., Liu, Y., and Zettlemoyer, L · 2019

Cited alongside, same era.

Levenshtein transformer

Original

Gu, J., Wang, C., and Zhao, J · 2019

Cited alongside, same era.

Discrete object generation with reversible inductive construction

Original

Seff, A., Zhou, W., Damani, F., Doyle, A., and Adams, R. P · 2019

Cited alongside, same era.

BERT has a mouth, and it must speak: BERT as a markov random field language model

Original

Wang, A. and Cho, K · 2019

Cited alongside, same era.

Learning to represent edits

Yin, P., Neubig, G., Allamanis, M., Brockschmidt, M., and Gaunt, A. L · 2019

Hoppity: Learning graph transformations to detect and fix bugs in programs

Dinella, E., Dai, H., Li, Z., Naik, M., Song, L., and Wang, K · 2020

Later among the works it cites.

Denoising diffusion probabilistic models

Original

Ho, J., Jain, A., and Abbeel, P · 2020

Later among the works it cites.

Exploring the limits of transfer learning with a unified text-to-text transformer

Original

Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2020

Later among the works it cites.

Insertion-deletion transformer

Original

Ruis, L., Stern, M., Proskurnia, J., and Chan, W · 2020

Later among the works it cites.

Structured denoising diffusion models in discrete state-spaces

Original