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Explicit Trajectory Diversity for RL-Based Post-Training of LLM Agents

Fu, Huaiyu et al.
arXiv (All) · Papers
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machine-learning
LLM agents often admit multiple high-quality solutions to the same task, differing in reasoning structure, tool-use pattern, or interaction trajectory. Yet existing notions of diversity in LLM post-training are mostly implicit, arising from general stochasticity and regularization mechanisms rather
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