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Germán Kruszewski
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2020 – today
- 2023
- [c21]Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman:
Should you marginalize over possible tokenizations? ACL (2) 2023: 1-12 - [c20]Germán Kruszewski, Jos Rozen, Marc Dymetman:
disco: a toolkit for Distributional Control of Generative Models. ACL (demo) 2023: 144-160 - [c19]Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman:
Aligning Language Models with Preferences through f-divergence Minimization. ICML 2023: 11546-11583 - [i20]Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman:
Aligning Language Models with Preferences through f-divergence Minimization. CoRR abs/2302.08215 (2023) - [i19]Germán Kruszewski, Jos Rozen, Marc Dymetman:
disco: a toolkit for Distributional Control of Generative Models. CoRR abs/2303.05431 (2023) - [i18]Nadezhda Chirkova, Germán Kruszewski, Jos Rozen, Marc Dymetman:
Should you marginalize over possible tokenizations? CoRR abs/2306.17757 (2023) - [i17]Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman:
Compositional preference models for aligning LMs. CoRR abs/2310.13011 (2023) - 2022
- [j4]Germán Kruszewski, Tomás Mikolov:
Emergence of Self-Reproducing Metabolisms as Recursive Algorithms in an Artificial Chemistry. Artif. Life 27(3-4): 277-299 (2022) - [j3]Bryan Eikema, Germán Kruszewski, Christopher R. Dance, Hady Elsahar, Marc Dymetman:
An approximate sampler for energy-based models with divergence diagnostics. Trans. Mach. Learn. Res. 2022 (2022) - [c18]Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman:
Controlling Conditional Language Models without Catastrophic Forgetting. ICML 2022: 11499-11528 - [c17]Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman:
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting. NeurIPS 2022 - [i16]Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman:
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting. CoRR abs/2206.00761 (2022) - 2021
- [i15]Germán Kruszewski, Tomás Mikolov:
Emergence of self-reproducing metabolisms as recursive algorithms in an Artificial Chemistry. CoRR abs/2103.08245 (2021) - [i14]Tomasz Korbak, Hady Elsahar, Marc Dymetman, Germán Kruszewski:
Energy-Based Models for Code Generation under Compilability Constraints. CoRR abs/2106.04985 (2021) - [i13]Matthias Gallé, Jos Rozen, Germán Kruszewski, Hady Elsahar:
Unsupervised and Distributional Detection of Machine-Generated Text. CoRR abs/2111.02878 (2021) - [i12]Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman:
Controlling Conditional Language Models with Distributional Policy Gradients. CoRR abs/2112.00791 (2021) - [i11]Bryan Eikema, Germán Kruszewski, Hady Elsahar, Marc Dymetman:
Sampling from Discrete Energy-Based Models with Quality/Efficiency Trade-offs. CoRR abs/2112.05702 (2021) - 2020
- [c16]Germán Kruszewski, Tomás Mikolov:
Combinatory Chemistry: Towards a Simple Model of Emergent Evolution. ALIFE 2020: 411-419 - [c15]Arta Cika, Elissa Cohen, Germán Kruszewski, Luther Seet, Patrick Steinmann, Wenqian Yin:
Resilient Life: An Exploration of Perturbed Autopoietic Patterns in Conway's Game of Life. ALIFE 2020: 656-664 - [i10]Germán Kruszewski, Tomás Mikolov:
Combinatory Chemistry: Towards a Simple Model of Emergent Evolution. CoRR abs/2003.07916 (2020) - [i9]Germán Kruszewski, Ionut-Teodor Sorodoc, Tomás Mikolov:
Class-Agnostic Continual Learning of Alternating Languages and Domains. CoRR abs/2004.03340 (2020)
2010 – 2019
- 2019
- [c14]Rezka Leonandya, Dieuwke Hupkes, Elia Bruni, Germán Kruszewski:
The Fast and the Flexible: Training Neural Networks to Learn to Follow Instructions from Small Data. IWCS (1) 2019: 223-234 - [c13]Yair Lakretz, Germán Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, Marco Baroni:
The emergence of number and syntax units in LSTM language models. NAACL-HLT (1) 2019: 11-20 - [c12]Serhii Havrylov, Germán Kruszewski, Armand Joulin:
Cooperative Learning of Disjoint Syntax and Semantics. NAACL-HLT (1) 2019: 1118-1128 - [i8]Serhii Havrylov, Germán Kruszewski, Armand Joulin:
Cooperative Learning of Disjoint Syntax and Semantics. CoRR abs/1902.09393 (2019) - [i7]Yair Lakretz, Germán Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, Marco Baroni:
The emergence of number and syntax units in LSTM language models. CoRR abs/1903.07435 (2019) - 2018
- [c11]Alexis Conneau, Germán Kruszewski, Guillaume Lample, Loïc Barrault, Marco Baroni:
What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties. ACL (1) 2018: 2126-2136 - [i6]Adam Liska, Germán Kruszewski, Marco Baroni:
Memorize or generalize? Searching for a compositional RNN in a haystack. CoRR abs/1802.06467 (2018) - [i5]Alexis Conneau, Germán Kruszewski, Guillaume Lample, Loïc Barrault, Marco Baroni:
What you can cram into a single vector: Probing sentence embeddings for linguistic properties. CoRR abs/1805.01070 (2018) - [i4]Dieuwke Hupkes, Anand Singh, Kris Korrel, Germán Kruszewski, Elia Bruni:
Learning compositionally through attentive guidance. CoRR abs/1805.09657 (2018) - [i3]Rezka Leonandya, Elia Bruni, Dieuwke Hupkes, Germán Kruszewski:
The Fast and the Flexible: training neural networks to learn to follow instructions from small data. CoRR abs/1809.06194 (2018) - 2017
- [c10]Marco Baroni, Armand Joulin, Allan Jabri, Germán Kruszewski, Angeliki Lazaridou, Klemen Simonic, Tomás Mikolov:
CommAI: Evaluating the first steps towards a useful general AI. ICLR (Workshop) 2017 - [i2]Marco Baroni, Armand Joulin, Allan Jabri, Germán Kruszewski, Angeliki Lazaridou, Klemen Simonic, Tomás Mikolov:
CommAI: Evaluating the first steps towards a useful general AI. CoRR abs/1701.08954 (2017) - 2016
- [b1]Germán Kruszewski:
Inference with Distributional Semantic Models. University of Trento, Italy, 2016 - [j2]Germán Kruszewski, Denis Paperno, Raffaella Bernardi, Marco Baroni:
There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics. Comput. Linguistics 42(4): 637-660 (2016) - [c9]Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, Raquel Fernández:
The LAMBADA dataset: Word prediction requiring a broad discourse context. ACL (1) 2016 - [c8]Ngoc-Quan Pham, Germán Kruszewski, Gemma Boleda:
Convolutional Neural Network Language Models. EMNLP 2016: 1153-1162 - [c7]Francesco Barbieri, Germán Kruszewski, Francesco Ronzano, Horacio Saggion:
How Cosmopolitan Are Emojis?: Exploring Emojis Usage and Meaning over Different Languages with Distributional Semantics. ACM Multimedia 2016: 531-535 - [i1]Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, Raquel Fernández:
The LAMBADA dataset: Word prediction requiring a broad discourse context. CoRR abs/1606.06031 (2016) - 2015
- [j1]Germán Kruszewski, Denis Paperno, Marco Baroni:
Deriving Boolean Structures from Distributional Vectors. Trans. Assoc. Comput. Linguistics 3: 375-388 (2015) - [c6]Nghia The Pham, Germán Kruszewski, Angeliki Lazaridou, Marco Baroni:
Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model. ACL (1) 2015: 971-981 - [c5]Germán Kruszewski, Marco Baroni:
So similar and yet incompatible: Toward the automated identification of semantically compatible words. HLT-NAACL 2015: 964-969 - 2014
- [c4]Marco Baroni, Georgiana Dinu, Germán Kruszewski:
Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors. ACL (1) 2014: 238-247 - [c3]Germán Kruszewski, Marco Baroni:
Dead parrots make bad pets: Exploring modifier effects in noun phrases. *SEM@COLING 2014: 171-181 - 2012
- [c2]Laura Perez-Beltrachini, Claire Gardent, Germán Kruszewski:
Generating Grammar Exercises. BEA@NAACL-HLT 2012: 147-156 - [c1]Claire Gardent, Germán Kruszewski:
Generation for Grammar Engineering. INLG 2012: 31-39
Coauthor Index
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