[HUGGINGFACE]score: 0.42
From VLM Planners to Robotic Agents: Self-Evolving Harnesses for History-Dependent Manipulation
October 20, 2026
An editable harness architecture transforms vision-language models into robotic agents by maintaining task context through history-dependent memory. This framework addresses non-Markovian dependencies in long-horizon manipulation, allowing high-level planners to refine decision-making based on execution experience and past interaction outcomes to mitigate error compounding.
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