Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.01446 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916821398978560 |
|---|---|
| author | Amer, Abd Elrahman Amer, Magdi |
| author_facet | Amer, Abd Elrahman Amer, Magdi |
| contents | Improving customer service quality and response time are critical factors for maintaining customer loyalty and increasing a company's market share. While adopting emerging technologies such as Large Language Models (LLMs) is becoming a necessity to achieve these goals, the risk of hallucination remains a major challenge. In this paper, we present a multi-agent system to handle customer requests sent via SMS. This system integrates LLM based agents with fuzzy logic to mitigate hallucination risks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01446 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Using multi-agent architecture to mitigate the risk of LLM hallucinations Amer, Abd Elrahman Amer, Magdi Artificial Intelligence Improving customer service quality and response time are critical factors for maintaining customer loyalty and increasing a company's market share. While adopting emerging technologies such as Large Language Models (LLMs) is becoming a necessity to achieve these goals, the risk of hallucination remains a major challenge. In this paper, we present a multi-agent system to handle customer requests sent via SMS. This system integrates LLM based agents with fuzzy logic to mitigate hallucination risks. |
| title | Using multi-agent architecture to mitigate the risk of LLM hallucinations |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2507.01446 |