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Ecom-RLVE: Adaptive Verifiable Environments for E-Commerce Conversational Agents

AI 摘要

Ecom-RLVE extends the RLVE framework to multi-turn, tool-augmented e-commerce conversations. EcomRLVE-GYM offers eight verifiable environments for tasks like product discovery and cart building, featuring procedural problem generation and a 12-axis difficulty curriculum. It uses algorithmically verifiable rewards, avoiding subjective LLM-as-a-judge evaluations. Early results with a Qwen 3 8B model trained with DAPO demonstrate that environment scaling and adaptive difficulty improve agentic task completion in real-world scenarios.

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收录当时偏移:UTC+02026年7月5日 04:00 UTC

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2026年7月5日 04:00
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