Papers by Adam Jelley
LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots (2025.coling-main)
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| Challenge: | Large language models have shown significant potential for robotics tasks, but a gap remains in personalization of LLMs to household preferences. |
| Approach: | They propose a framework to personalize LLM planners for household robotics . they use imitation learning and reinforced self-training to personalise the planner . |
| Outcome: | The proposed framework performs iterative planning in multi-room, partially-observable household environments, utilizing a scene graph built dynamically from local observations. |