5 papers
Reducing Hallucination in Enterprise AI Workflows via Hybrid Utility Minimum Bayes Risk (HUMBR)
Chenhao Fang, Jordi Mola, Mark Harman +10
Although LLMs drive automation, it is critical to ensure immense consideration for high-stakes enterprise workflows such as those involving legal matters, risk management, and priv…
AudioGuard: Toward Comprehensive Audio Safety Protection Across Diverse Threat Models
Mintong Kang, Chen Fang, Bo Li
Audio has rapidly become a primary interface for foundation models, powering real-time voice assistants. Ensuring safety in audio systems is inherently more complex than just "unsa…
Compliance Brain Assistant: Conversational Agentic AI for Assisting Compliance Tasks in Enterprise Environments
Shitong Zhu, Chenhao Fang, Derek Larson +8
This paper presents Compliance Brain Assistant (CBA), a conversational, agentic AI assistant designed to boost the efficiency of daily compliance tasks for personnel in enterprise…
Privacy Artifact ConnecTor (PACT): Embedding Enterprise Artifacts for Compliance AI Agents
Chenhao Fang, Yanqing Peng, Rajeev Rao +6
Enterprise environments contain a heterogeneous, rapidly growing collection of internal artifacts related to code, data, and many different tools. Critical information for assessin…
Ingest-And-Ground: Dispelling Hallucinations from Continually-Pretrained LLMs with RAG
Chenhao Fang, Derek Larson, Shitong Zhu +9
This paper presents new methods that have the potential to improve privacy process efficiency with LLM and RAG. To reduce hallucination, we continually pre-train the base LLM model…