U-Define improves user control in LLM planning by letting people define hard rules and soft preferences in natural language with matching verification methods, raising usefulness and satisfaction scores.
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cs.AI 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
RAMP learns numeric action models online via a DRL-planning feedback loop and outperforms PPO on IPC numeric domains in solvability and plan quality.
citing papers explorer
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U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning
U-Define improves user control in LLM planning by letting people define hard rules and soft preferences in natural language with matching verification methods, raising usefulness and satisfaction scores.
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RAMP: Hybrid DRL for Online Learning of Numeric Action Models
RAMP learns numeric action models online via a DRL-planning feedback loop and outperforms PPO on IPC numeric domains in solvability and plan quality.