35 citations · 38 across the 7 of their papers we have counts for
4 papers · 1 filter
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations
Aryo Pradipta Gema, Chen Jin, Ahmed Abdulaal +5
Large Language Models (LLMs) often hallucinate, producing unfaithful or factually incorrect outputs by misrepresenting the provided context or incorrectly recalling internal knowle…
Edinburgh Clinical NLP at MEDIQA-CORR 2024: Guiding Large Language Models with Hints
Aryo Pradipta Gema, Chaeeun Lee, Pasquale Minervini +3
The MEDIQA-CORR 2024 shared task aims to assess the ability of Large Language Models (LLMs) to identify and correct medical errors in clinical notes. In this study, we evaluate the…
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4
Aryo Pradipta Gema, Giwon Hong, Pasquale Minervini +2
The NLI4CT task assesses Natural Language Inference systems in predicting whether hypotheses entail or contradict evidence from Clinical Trial Reports. In this study, we evaluate v…
Can GPT-3.5 Generate and Code Discharge Summaries?
Matúš Falis, Aryo Pradipta Gema, Hang Dong +6
Objective: To investigate GPT-3.5 in generating and coding medical documents with ICD-10 codes for data augmentation on low-resources labels. Materials and Methods: Employing GPT-3…