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ORCIDVíctor Gallego
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Journal Articles
- 2021
[j2]Víctor Gallego
, David Ríos Insua:
Variationally Inferred Sampling through a Refined Bound. Entropy 23(1): 123 (2021)- 2016
- [j1]Carlos Calvo, José Antonio Villacorta-Atienza, V. I. Mironov, Víctor Gallego, Valeri A. Makarov:
Waves in isotropic Totalistic Cellular Automata: Application to Real-Time robot Navigation. Adv. Complex Syst. 19(4-5): 1650012:1-1650012:18 (2016)
Conference and Workshop Papers
- 2024
- [c2]Víctor Gallego:
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective. Tiny Papers @ ICLR 2024 - 2019
- [c1]Víctor Gallego, Roi Naveiro, David Ríos Insua:
Reinforcement Learning under Threats. AAAI 2019: 9939-9940
Informal and Other Publications
- 2024
- [i17]Víctor Gallego:
Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs. CoRR abs/2402.08005 (2024) - [i16]Víctor Gallego:
Configurable Safety Tuning of Language Models with Synthetic Preference Data. CoRR abs/2404.00495 (2024) - [i15]Víctor Gallego:
Merging Improves Self-Critique Against Jailbreak Attacks. CoRR abs/2406.07188 (2024) - 2023
- [i14]Víctor Gallego:
ZYN: Zero-Shot Reward Models with Yes-No Questions. CoRR abs/2308.06385 (2023) - [i13]Víctor Gallego:
Fast Adaptation with Bradley-Terry Preference Models in Text-To-Image Classification and Generation. CoRR abs/2308.07929 (2023) - [i12]Víctor Gallego:
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective. CoRR abs/2312.01957 (2023) - 2022
- [i11]Manuel Navarro-García, Daniel Precioso, Kathryn Gavira-O'Neill, Alberto Torres-Barrán, David Gordo, Víctor Gallego, David Gómez-Ullate:
How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patterns. CoRR abs/2207.07049 (2022) - [i10]Víctor Gallego:
Personalizing Text-to-Image Generation via Aesthetic Gradients. CoRR abs/2209.12330 (2022) - 2021
- [i9]Víctor Gallego, Roi Naveiro, David Ríos Insua, Wolfram Rozas:
Data sharing games. CoRR abs/2101.10721 (2021) - [i8]Víctor Gallego:
Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning. CoRR abs/2109.13232 (2021) - 2020
- [i7]David Ríos Insua, Roi Naveiro, Víctor Gallego, Jason Poulos:
Adversarial Machine Learning: Perspectives from Adversarial Risk Analysis. CoRR abs/2003.03546 (2020) - [i6]Víctor Gallego, Roi Naveiro, Alberto Redondo, David Ríos Insua, Fabrizio Ruggeri:
Protecting Classifiers From Attacks. A Bayesian Approach. CoRR abs/2004.08705 (2020) - [i5]David Banks, Víctor Gallego, Roi Naveiro, David Ríos Insua:
Adversarial Risk Analysis (Overview). CoRR abs/2007.02613 (2020) - 2019
- [i4]Víctor Gallego, Roi Naveiro, David Ríos Insua, David Gómez-Ullate:
Opponent Aware Reinforcement Learning. CoRR abs/1908.08773 (2019) - [i3]Víctor Gallego, David Ríos Insua:
Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs. CoRR abs/1908.09744 (2019) - 2018
- [i2]Víctor Gallego, Roi Naveiro, David Ríos Insua:
Reinforcement Learning under Threats. CoRR abs/1809.01560 (2018) - [i1]Víctor Gallego, David Ríos Insua:
Stochastic Gradient MCMC with Repulsive Forces. CoRR abs/1812.00071 (2018)
Coauthor Index
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