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Utilizing Large Language Models for Automating Technical Customer Support

2024-06-03 · Jochen Wulf, Jürg Meierhofer

The use of large language models (LLMs) such as OpenAI's GPT-4 in technical customer support (TCS) has the potential to revolutionize this area. This study examines automated text correction, summarization of customer inquiries and question answering using LLMs. Through prototypes and data analyses, the potential and challenges of integrating LLMs into the TCS will be demonstrated. Our results show promising approaches for improving the efficiency and quality of customer service through LLMs, but also emphasize the need for quality-assured implementation and organizational adjustments in the data ecosystem.

📄 PDF Abstract BibTeX arXiv:2406.01407

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Question Answering

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customer support 설명 없음
Golden Queue Managers 설명 없음
Attention 설명 없음
Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
Layer Normalization Unlike batch normalization, Layer Normalization directly estimates the normalization statistics from the summed inputs…
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Position-Wise Feed-Forward Layer 설명 없음
BPE Byte Pair Encoding, or BPE, is a subword segmentation algorithm that encodes rare and unknown words as sequences of subword units. The intuition is that various word…

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