Researchers have developed ProfiLLM, a novel agentic LLM data pipeline designed to enhance industrial ride-hailing dispatch systems. This system addresses challenges in processing massive datasets by using tool-augmented knowledge mining and utility-aligned profile exploration. When deployed on DiDi's platform, ProfiLLM demonstrated significant improvements, including a +6.14% relative AUC increase in outcome prediction and a +4.35% GMV gain in simulations. AI
IMPACT Proposes a novel method for applying LLMs to large-scale industrial data, potentially improving efficiency in logistics and dispatch systems.
RANK_REASON This is a research paper detailing a new method for applying LLMs to a specific industrial problem.
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- DiDi
- Direct Preference Optimization
- Gotit.pub
- Hugging Face
- large-language models
- ProfiLLM
- ScienceCast
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