Hi Hugging Face community 
I’m excited to share my recent research work published at AIS2C2 2025.
Paper: Prompt-Driven Tool-Calling for Lightweight Open Source LLMs
This research explores how lightweight open-source LLMs can perform complex tasks using a prompt-driven tool-calling framework, without relying on large proprietary models.
Problem Statement
Most small LLMs struggle with:
- Multi-step reasoning
- Tool usage (APIs, calculators, search tools)
- Complex task decomposition
Large models solve this, but they are expensive and not always deployable.
Proposed Idea
We introduce a prompt-driven approach that enables LLMs to:
- Decide when to use tools
- Select appropriate tools dynamically
- Chain multiple reasoning steps
- Reduce dependency on large models
Key Benefits
- Works with lightweight open-source LLMs
- Reduces compute requirements
- Enables AI agent-like behavior
- Practical for real-world deployment
Paper Link
https://www.aiscindia.co.in/wp-content/uploads/2026/06/ilovepdf_merged-4.pdf
Looking for Feedback
I would love feedback from the community on:
- Better tool-calling strategies
- Improvements for lightweight agents
- Open-source implementations
Publication Details
Published in: AIS2C2 2025
Pages: 493–497
Thank you!
