# LLM-Based Insight Extraction for Contact Center Analytics and Cost-Efficient Deployment

arXiv: https://arxiv.org/abs/2503.19090 · HTML: https://mlsanity.com/paper/2503.19090/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 23 references that are in the map.
- First posted on arXiv 24 Mar 2025.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers](https://mlsanity.com/paper/2210.17323/) (2022)
- [Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators](https://mlsanity.com/paper/2404.04475/) (2024)
- [SummEval: Re-evaluating Summarization Evaluation](https://mlsanity.com/paper/2007.12626/) (2020)
- [Annotation Artifacts in Natural Language Inference Data](https://mlsanity.com/paper/1803.02324/) (2018)
- [LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://mlsanity.com/paper/2403.12968/) (2024)
- [Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation](https://mlsanity.com/paper/2212.07981/) (2022)
- [Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling](https://mlsanity.com/paper/2012.07311/) (2020)
- [Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation](https://mlsanity.com/paper/2105.09235/) (2021)
- [Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loop](https://mlsanity.com/paper/2211.01354/) (2022)
- [Developing a Production System for Purpose of Call Detection in Business Phone Conversations](https://mlsanity.com/paper/2205.06904/) (2022)
- [Machine Translation Evaluation using Bi-directional Entailment](https://mlsanity.com/paper/1911.00681/) (2019)
- [Entity-level Sentiment Analysis in Contact Center Telephone Conversations](https://mlsanity.com/paper/2210.13401/) (2022)

## Built on by (most cited first, 1 of 1)

- [AgentBalance: Backbone-then-Topology Design for Cost-Effective Multi-Agent Systems under Budget Constraints](https://mlsanity.com/paper/2512.11426/) (2025)

## Abstract (arXiv)

Large Language Models have transformed the Contact Center industry, manifesting in enhanced self-service tools, streamlined administrative processes, and augmented agent productivity. This paper delineates our system that automates call driver generation, which serves as the foundation for tasks such as topic modeling, incoming call classification, trend detection, and FAQ generation, delivering actionable insights for contact center agents and administrators to consume. We present a cost-efficient LLM system design, with 1) a comprehensive evaluation of proprietary, open-weight, and fine-tuned models and 2) cost-efficient strategies, and 3) the corresponding cost analysis when deployed in production environments.