TripScore: Aligning LLMs for Real-World Travel Planning via Expert-Calibrated Reward
TripScore is presented, a behavior-grounded benchmark and evaluation framework built from real user logs and calibrated against 1,468 pairwise judgments by 203 travel experts that finds that reinforcement learning fine-tuning provides consistent gains over other approaches under the same base model and practical latenc...
Yin-Cen Qu, Huan Xiao, Feng Li et al.
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