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Asma Ben Abacha

6 accepted papers

2025

A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment

ACL 2025long

High computation costs and latency of large language models such as GPT-4 have limited their deployment in clinical settings. Small language models (SLMs) offer a cost-effective alternative, but their limited capacity requires biomedical domain adaptation, which remains challenging. An additional bo…

Cited by 0SourcePDFScholar
2025

MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes

ACL 2025finding

Several studies have shown that Large Language Models (LLMs) can answer medical questions correctly, even outperforming the average human score in some medical exams. However, to our knowledge, no study has been conducted to assess the ability of language models to validate existing or generated med…

2024

To Err Is Human, How about Medical Large Language Models? Comparing Pre-trained Language Models for Medical Assessment Errors and Reliability

COLING 2024main

Unpredictability, especially unpredictability with unknown error characteristics, is a highly undesirable trait, particularly in medical patient care applications. Although large pre-trained language models (LLM) have been applied to a variety of unseen tasks with highly competitive and successful r…

2023

An Investigation of Evaluation Methods in Automatic Medical Note Generation

ACL 2023findings

Recent studies on automatic note generation have shown that doctors can save significant amounts of time when using automatic clinical note generation (Knoll et al., 2022). Summarization models have been used for this task to generate clinical notes as summaries of doctor-patient conversations (Kris…

2021

Evidence-based Fact-Checking of Health-related Claims

EMNLP 2021finding

The task of verifying the truthfulness of claims in textual documents, or fact-checking, has received significant attention in recent years. Many existing evidence-based factchecking datasets contain synthetic claims and the models trained on these data might not be able to verify real-world claims.…

2021

Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards

ACL 2021short

The growth of online consumer health questions has led to the necessity for reliable and accurate question answering systems. A recent study showed that manual summarization of consumer health questions brings significant improvement in retrieving relevant answers. However, the automatic summarizati…