4 papers · 1 filter
From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization
Qianqi Yan, Huy Nguyen, Sumana Srivatsa +3
Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where each statement originates-and a m…
Optimizing Long-Form Clinical Text Generation with Claim-Based Rewards
Samyak Jhaveri, Praphul Singh, Jangwon Kim +2
Automating clinical documentation with large language models requires precise alignment with priorities such as completeness and factual grounding. We present an evaluation-integra…
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey
Bo Ni, Zheyuan Liu, Leyao Wang +17
Retrieval-Augmented Generation (RAG) is an advanced technique designed to address the challenges of Artificial Intelligence-Generated Content (AIGC). By integrating context retriev…
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)
Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly
With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes domains, ensuring the trustworthiness, safety, and observability of these systems has b…