Zobrazeno 1 - 10
of 5 912
pro vyhledávání: '"Pergola, A"'
Autor:
Lyu, Chen, Pergola, Gabriele
Biomedical literature is often written in highly specialized language, posing significant comprehension challenges for non-experts. Automatic text simplification (ATS) offers a solution by making such texts more accessible while preserving critical i
Externí odkaz:
http://arxiv.org/abs/2410.09632
Autor:
Lyu, Chen, Pergola, Gabriele
Medical text simplification is crucial for making complex biomedical literature more accessible to non-experts. Traditional methods struggle with the specialized terms and jargon of medical texts, lacking the flexibility to adapt the simplification p
Externí odkaz:
http://arxiv.org/abs/2410.09631
Predicting unknown drug-drug interactions (DDIs) is crucial for improving medication safety. Previous efforts in DDI prediction have typically focused on binary classification or predicting DDI categories, with the absence of explanatory insights tha
Externí odkaz:
http://arxiv.org/abs/2409.05592
Generating event graphs from long documents is challenging due to the inherent complexity of multiple tasks involved such as detecting events, identifying their relationships, and reconciling unstructured input with structured graphs. Recent studies
Externí odkaz:
http://arxiv.org/abs/2406.18449
Drug safety research is crucial for maintaining public health, often requiring comprehensive data support. However, the resources currently available to the public are limited and fail to provide a comprehensive understanding of the relationship betw
Externí odkaz:
http://arxiv.org/abs/2407.01585
Pathology reports are rich in clinical and pathological details but are often presented in free-text format. The unstructured nature of these reports presents a significant challenge limiting the accessibility of their content. In this work, we prese
Externí odkaz:
http://arxiv.org/abs/2405.02040
Event temporal graphs have been shown as convenient and effective representations of complex temporal relations between events in text. Recent studies, which employ pre-trained language models to auto-regressively generate linearised graphs for const
Externí odkaz:
http://arxiv.org/abs/2404.01532
With the advent of large language models (LLMs), there has been growing interest in exploring their potential for medical applications. This research aims to investigate the ability of LLMs, specifically ChatGPT, in the context of pharmacovigilance e
Externí odkaz:
http://arxiv.org/abs/2402.15663
Autor:
Abriola, Davide, Della Pergola, Daniele, Lombardi, Marco, Bergamini, Pietro, Nonino, Mario, Grillo, Claudio, Rosati, Piero
We present a new weak lensing analysis of the Hubble Frontier Fields galaxy cluster Abell 2744 ($z$ = 0.308) using new Magellan/MegaCam multi-band $gri$ imaging data. We carry out our study by applying brand-new PSF and shape measurement softwares th
Externí odkaz:
http://arxiv.org/abs/2402.08364
Autor:
Lu, Junru, An, Siyu, Lin, Mingbao, Pergola, Gabriele, He, Yulan, Yin, Di, Sun, Xing, Wu, Yunsheng
We propose MemoChat, a pipeline for refining instructions that enables large language models (LLMs) to effectively employ self-composed memos for maintaining consistent long-range open-domain conversations. We demonstrate a long-range open-domain con
Externí odkaz:
http://arxiv.org/abs/2308.08239