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cs.CL2026
Toward Better Assessment of LLMs' Performance in Clinical Error Detection
Yifan Zhang, Rahmatollah Beheshti
Automated detection of errors in clinical documentation is a promising application of large language models (LLMs), yet decisions to deploy such models rest on benchmarks that eval…
cs.CL2026
AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Fahmida Liza Piya, Rahmatollah Beheshti
Large language models (LLMs) offer substantial promise for automating clinical text summarization, yet maintaining factual consistency remains challenging due to the length, noise,…