2 citations · 3 across the 3 of their papers we have counts for
3 papers
Meaning Typed Prompting: A Technique for Efficient, Reliable Structured Output Generation
Chandra Irugalbandara
Extending Large Language Models (LLMs) to advanced applications requires reliable structured output generation. Existing methods which often rely on rigid JSON schemas, can lead to…
MTP: A Meaning-Typed Language Abstraction for AI-Integrated Programming
Jayanaka L. Dantanarayana, Yiping Kang, Kugesan Sivasothynathan +6
Software development is shifting from traditional programming to AI-integrated applications that leverage generative AI and large language models (LLMs) during runtime. However, in…
Scaling Down to Scale Up: A Cost-Benefit Analysis of Replacing OpenAI's LLM with Open Source SLMs in Production
Chandra Irugalbandara, Ashish Mahendra, Roland Daynauth +6
Many companies use large language models (LLMs) offered as a service, like OpenAI's GPT-4, to create AI-enabled product experiences. Along with the benefits of ease-of-use and shor…