Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)
Author:
Affiliation:
1. Oracle Health AI, Redwood City, CA, USA
2. Microsoft Azure AI, Boston, MA, USA
3. Google Cloud AI, Sunnyvale, CA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3637528.3671467
Reference137 articles.
1. Martin Abadi Andy Chu Ian Goodfellow H Brendan McMahan Ilya Mironov Kunal Talwar and Li Zhang. 2016. Deep learning with differential privacy. In CCS.
2. AI model disgorgement: Methods and choices
3. Google Cloud AI. 2024. Check grounding | Vertex AI Agent Builder. https: //cloud.google.com/generative-ai-app-builder/docs/check-grounding
4. Microsoft Azure AI. 2024. Groundedness detection. https://learn.microsoft. com/en-us/azure/ai-services/content-safety/quickstart-groundedness
5. Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2024. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection. In The Twelfth International Conference on Learning Representations.
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