12 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.CL2024
SLM Meets LLM: Balancing Latency, Interpretability and Consistency in Hallucination Detection
Mengya Hu, Rui Xu, Deren Lei +5
Large language models (LLMs) are highly capable but face latency challenges in real-time applications, such as conducting online hallucination detection. To overcome this issue, we…
cs.CL2023★ 2 cited
A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications
Ahmed Magooda, Alec Helyar, Kyle Jackson +14
We present a framework for the automated measurement of responsible AI (RAI) metrics for large language models (LLMs) and associated products and services. Our framework for automa…
cs.CL2023★ 12 cited
Chain of Natural Language Inference for Reducing Large Language Model Ungrounded Hallucinations
Deren Lei, Yaxi Li, Mengya Hu +4
Large language models (LLMs) can generate fluent natural language texts when given relevant documents as background context. This ability has attracted considerable interest in dev…