Felipe Llinares-López

◀ ▶ joint publications with Mathieu Blondel

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Publications

2024
[i11]
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  - journals/corr/abs-2402-02992
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  - https://dblp.org/rec/journals/corr/abs-2402-02992
Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel:
Decoding-time Realignment of Language Models. CoRR abs/2402.02992 (2024)
[i10]
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  - journals/corr/abs-2402-04792
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Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Ramé, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel:
Direct Language Model Alignment from Online AI Feedback. CoRR abs/2402.04792 (2024)
[i9]
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  - journals/corr/abs-2402-05468
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Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet:
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR abs/2402.05468 (2024)
2022
[c7]
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  - conf/nips/BlondelBCFHLPV22
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Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. NeurIPS 2022
[c6]
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  - conf/nips/BlondelLDHG22
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Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Léonard Hussenot, Matthieu Geist:
Learning Energy Networks with Generalized Fenchel-Young Losses. NeurIPS 2022
[i7]
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  - journals/corr/abs-2205-09589
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Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Léonard Hussenot, Matthieu Geist:
Learning Energy Networks with Generalized Fenchel-Young Losses. CoRR abs/2205.09589 (2022)
2021
[i6]
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  - journals/corr/abs-2105-15183
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Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. CoRR abs/2105.15183 (2021)

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