Filtering Harmful Actions Isn't Enough: Phantom Transfer in Agentic SDF

Synthetic data is widely used to train large language models because it is inexpensive to generate and easy to control. As models are increasingly deployed as agents, synthetic trajectories are likely to become an important source of training data for agentic behavior.

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• llms
• agents
• reinforcement-learning
• fine-tuning
• benchmarks
• safety