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Test-Time Policy Adaptation for Enhanced Multi-Turn Interactions with LLMs

This work proposes a new paradigm: Test-Time Policy Adaptation for Multi-Turn Interactions (T2PAM), which utilizes user feedback from the ongoing interaction as a reward signal to estimate a latent optimal policy aligned with user preferences, then updates a small subset of parameters to steer the model toward this pol...

Chen-Xing Wei, Hong Wang, Ying He et al. · 4 citations

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