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Local Qwen model struggles with return policy application

A local instance of the Qwen3.8:27b model, accessed via Ollama, demonstrated limitations when tasked with applying return policies to customer inquiries. The model struggled with cases where crucial information, such as receipt dates or the nature of the item (opened vs. unopened), was missing or ambiguous. In one instance, the model generated a response that cited a 14-day warranty period despite the provided policies only mentioning return windows and not warranties. Furthermore, the model sometimes produced conflicting drafts within a single response, first stating an incorrect policy and then revising itself to a more accurate one, highlighting potential issues for automated customer service pipelines. AI

IMPACT Demonstrates the need for robust error handling and data validation in LLM-powered customer service applications.

RANK_REASON The item details the performance of a specific LLM in a practical application, highlighting its limitations and potential failure modes.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Local Qwen model struggles with return policy application

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20 / 100
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Tool
The item details the performance of a specific LLM in a practical application, highlighting its limitations and potential failure modes.
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product, other
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · weiche chiu ·

    My Local Model Chose a Return Policy Too Early. Code Can Take Over Part of That Step

    <p>I asked a local model how long the warranty was. The sources I gave it were two versions of a return policy. Neither mentions a warranty. It checked the dates, picked one of the return policies, and wrote:</p> <blockquote> <p>Therefore, the warranty duration (review window) is…