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Lucas Torroba Hennigen
Lucas Torroba Hennigen
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
SIGMORPHON 2020 shared task 0: Typologically diverse morphological inflection
E Vylomova, J White, E Salesky, SJ Mielke, S Wu, E Ponti, RH Maudslay, ...
SIGMORPHON, 2020
582020
Intrinsic probing through dimension selection
L Torroba Hennigen, A Williams, R Cotterell
EMNLP, 2020
48*2020
Learning to grow pretrained models for efficient transformer training
P Wang, R Panda, L Torroba Hennigen, P Greengard, L Karlinsky, R Feris, ...
ICLR, 2023
292023
UniMorph 4.0: Universal morphology
K Batsuren, O Goldman, S Khalifa, N Habash, W Kieraś, G Bella, ...
LREC, 2022
232022
Same neurons, different languages: Probing morphosyntax in multilingual pre-trained models
K Stańczak, E Ponti, L Torroba Hennigen, R Cotterell, I Augenstein
NAACL, 2022
212022
Probing as quantifying inductive bias
A Immer, L Torroba Hennigen, V Fortuin, R Cotterell
ACL, 2022
19*2022
A measure-theoretic characterization of tight language models
L Du, L Torroba Hennigen, T Pimentel, C Meister, J Eisner, R Cotterell
ACL, 2022
182022
Machine reading of historical events
O Honovich, L Torroba Hennigen, O Abend, SB Cohen
ACL, 2020
92020
Classifying dyads for militarized conflict analysis
N Stoehr, L Torroba Hennigen, S Ahbab, R West, R Cotterell
EMNLP, 2021
82021
An ordinal latent variable model of conflict intensity
N Stoehr, L Torroba Hennigen, J Valvoda, R West, R Cotterell, A Schein
ACL, 2023
72023
Deriving language models from masked language models
L Torroba Hennigen, Y Kim
ACL, 2023
7*2023
Generalizing backpropagation for gradient-based interpretability
K Du, L Torroba Hennigen, N Stoehr, A Warstadt, R Cotterell
ACL, 2023
32023
A latent-variable model for intrinsic probing
K Stańczak, L Torroba Hennigen, A Williams, R Cotterell, I Augenstein
AAAI, 2022
32022
Towards verifiable text generation with symbolic references
L Torroba Hennigen, S Shen, A Nrusimha, B Gapp, D Sontag, Y Kim
arXiv preprint arXiv:2311.09188, 2023
12023
Principled gradient-based Markov chain Monte Carlo for text generation
L Du, A Amini, L Torroba Hennigen, XV Yu, J Eisner, H Lee, R Cotterell
arXiv preprint arXiv:2312.17710, 2023
2023
Principled Gradient-Based MCMC for Conditional Sampling of Text
L Du, A Amini, LT Hennigen, H Lee, J Eisner, R Cotterell
Forty-first International Conference on Machine Learning, 0
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Articles 1–16