3 papers
cs.CL2026
Towards Multidisciplinary Summarization of Hospital Stays: Efficient Sentence-Level Clinical Provenance Categorization
Baris Karacan, Vaibhav Bhargava, Barbara Di Eugenio +21
Effective "all-team" summarization in high-complexity settings like the Neonatal Intensive Care Unit (NICU) requires aggregating insights from diverse disciplines (physicians, nurs…
cs.CL2026
What Do LLMs Know About Alzheimer's Disease? Multi-loss Fine-Tuning and Probing for AD Detection
Lei Jiang, Yue Zhou, Natalie Parde
Reliable early detection of Alzheimer's disease (AD) is challenging, particularly due to the limited availability of labeled data. While large language models (LLMs) have shown str…
cs.CL2026
Context-Aware Counterfactual Data Augmentation for Gender Bias Mitigation in Language Models
Shweta Parihar, Liu Guangliang, Natalie Parde +1
A challenge in mitigating social bias in fine-tuned language models (LMs) is the potential reduction in language modeling capability, which can harm downstream performance. Counter…