Think&Cite uses self-guided Monte Carlo tree search and progress reward modeling to improve attributed text generation, reporting gains on ASQA, QAMPARI, and ELI5.
Lucas, Peter I
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Think&Cite: Improving Attributed Text Generation with Self-Guided Tree Search and Progress Reward Modeling
Think&Cite uses self-guided Monte Carlo tree search and progress reward modeling to improve attributed text generation, reporting gains on ASQA, QAMPARI, and ELI5.