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It is found that student-induced histories paired with teacher-generated action prefixes generally provide the strongest standalone training signal, whereas following the student at both levels generally performs worst, and fully on-policy data becomes beneficial when incorporated into a mixture with other configuratio...
The approach employs an iterative process where the agent collects new experiences, receives corrective feedback from humans in the form of hints, and integrates this feedback into its weights via a context distillation training procedure, which demonstrates the efficacy of the approach by implementing it in a Llama-3-...
ViPlan domains capture fundamental shortcomings of both VLM-grounded symbolic approaches and direct VLM planning methods, and is presented, the first open-source benchmark for comparing VLM-grounded symbolic approaches (VLM-as-grounder) with direct VLM planning methods (VLM-as-planner).
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