Papers by Mark Purcell
A Perspective on LLM Data Generation with Few-shot Examples: from Intent to Kubernetes Manifest (2025.acl-industry)
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| Challenge: | Large Language Models (LLMs) have transformed how complex tasks can be automated . traditional cloud computing operations involve complex manual configurations . |
| Approach: | They propose a pipeline for generating K8s manifests directly from user-described intents expressed in natural language using LLMs. |
| Outcome: | The proposed pipeline can generate K8s manifests directly from user-described intents expressed in natural language using LLMs. |
Granite Guardian: Comprehensive LLM Safeguarding (2025.naacl-industry)
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Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre Dognin, Keerthiram Murugesan, Erik Miehling, Martín Santillán Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
| Challenge: | a suite of advanced models is designed to detect and mitigate risks associated with prompts and responses. |
| Approach: | a team of researchers develop a model family to detect and mitigate risks associated with prompts and responses. the model family is based on the Granite 3.0 language models. |
| Outcome: | a new model family is designed to detect and mitigate risks associated with prompts and responses. |