24 citations · 120 across the 27 of their papers we have counts for
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cs.CL2024
Merging Improves Self-Critique Against Jailbreak Attacks
Victor Gallego
The robustness of large language models (LLMs) against adversarial manipulations, such as jailbreak attacks, remains a significant challenge. In this work, we propose an approach t…
cs.CL2024
Configurable Safety Tuning of Language Models with Synthetic Preference Data
Victor Gallego
State-of-the-art language model fine-tuning techniques, such as Direct Preference Optimization (DPO), restrict user control by hard-coding predefined behaviors into the model. To a…
cs.CL2024
Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs
Víctor Gallego
In this paper, we introduce \emph{refined Direct Preference Optimization} (rDPO), a method for improving the behavioral alignment of Large Language Models (LLMs) without the need f…