Papers by Inge Vejsbjerg
Granite Guardian: Comprehensive LLM Safeguarding (2025.naacl-industry)
Copied to clipboard
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. |
Towards Protecting Vital Healthcare Programs by Extracting Actionable Knowledge from Policy (2021.findings-acl)
Copied to clipboard
Vanessa Lopez, Nagesh Yadav, Gabriele Picco, Inge Vejsbjerg, Eoin Carrol, Seamus Brady, Marco Luca Sbodio, Lam Thanh Hoang, Miao Wei, John Segrave
| Challenge: | In the U.S., an estimated annual amount of USD$20-30B is lost to Fraud, Waste and abuse (FWA) |
| Approach: | They propose a method for automatically extracting knowledge from healthcare policy documents into a semantically-meaningful knowledge graph of rules. |
| Outcome: | The proposed method fuses advances in dependency parsing with a policy ontology to transform the content of regulatory healthcare policy into human-friendly policy rules with human oversight. |
AI Steerability 360: A Toolkit for Steering Large Language Models (2026.acl-demo)
Copied to clipboard
Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Ching-Yun Ko, Pierre Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney
| Challenge: | The AI Steerability 360 toolkit is an extensible, open-source Python library for steering LLMs. |
| Approach: | The AI Steerability 360 toolkit is an extensible, open-source Python library for steering LLMs. |
| Outcome: | The toolkit is available under an Apache 2.0 license and is available on https://github.com/IBM/AISteer360. |