arXiv (All)
open access
TripScore: Aligning LLMs for Real-World Travel Planning via Expert-Calibrated Reward
In our deployed travel-planning service, most users give minimal inputs or free-form requests rather than the structured constraint checklists assumed by existing benchmarks. We therefore present TripScore, a behavior-grounded benchmark and evaluation framework built from real user logs and calibrat
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ArgGYM: A Procedural, Engine-Verified Benchmark for Structured Defeasible Reasoning#1143010
- MA-SAPO: Multi-Agent Reasoning for Score-Aware Prompt Optimization#1118430
- E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch#1169651
- E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch#1142936
- Beyond Prompt or Skill? Attribution-Guided Optimization of Modular LLM Programs#1116823
Record · ID 1014558
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive