Jul 24, 2023 · Abstract:We propose Reinforcement Learning from Contrastive Distillation (RLCD), a method for aligning language models to follow principles ...
Nov 15, 2023 · The paper introduces Reinforcement Learning from Contrastive Distillation (RLCD), a novel method to align language models with human values without relying on ...
RLCD: Reinforcement Learning from Contrast Distillation - GitHub
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RLCD is a simple and effective way to simulate preference data generation for RLHF-based LLM alignment pipelines, comparing favorably to RLAIF and context ...
We propose Reinforcement Learning from Contrastive Distillation (RLCD), a method for aligning language models to follow principles expressed in natural language ...
Jul 14, 2024 · RLCD is a method developed to adjust language models to human preferences without using human feedback data.
View recent discussion. Abstract: We propose Reinforcement Learning from Contrastive Distillation (RLCD), a method for aligning language models to follow ...
Jul 24, 2023 · We propose Reinforcement Learning from Contrast Distillation (RLCD), a method for aligning language models to follow natural language principles ...
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Jul 24, 2023 · Reinforcement Learning from Contrastive Distillation (RLCD), a method for aligning language models to follow principles expressed in natural ...
RLCD: Reinforcement Learning From Contrastive. Distillation For Language Model Alignment ... Our method: RL From Contrastive Distillation. Human: Joe is so ...
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Jun 16, 2024 · Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.
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