Trained Miniatures: Low cost, High Efficacy SLMs for Sales & Marketing
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Abstract (arXiv)
Large language models (LLMs) excel in text generation; however, these creative elements require heavy computation and are accompanied by a steep cost. Especially for targeted applications such as sales and marketing outreach, these costs are far from feasible. This paper introduces the concept of "Trained Miniatures" - Small Language Models(SLMs) fine-tuned for specific, high-value applications, generating similar domain-specific responses for a fraction of the cost.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 16 references that are in the map. First posted on arXiv 21 Aug 2025.
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References · 12
- 2017Attention Is All You Needcited by 60,361
- 2015Distilling the Knowledge in a Neural Networkcited by 10,324
- 2020Scaling Laws for Neural Language Modelscited by 6,586
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
- 2020MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devicescited by 482
- 2025Small Language Models are the Future of Agentic AIcited by 270
- 2024Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classificationcited by 70
- 2024Language Models for Text Classification: Is In-Context Learning Enough?cited by 40
- 2024Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performancecited by 18
- 2024Smaller Language Models Are Better Instruction Evolverscited by 6
- 2025Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflowscited by 6
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