67 citations · 124 across the 6 of their papers we have counts for
6 papers
Controllable Synthetic Clinical Note Generation with Privacy Guarantees
Tal Baumel, Andre Manoel, Daniel Jones +5
In the field of machine learning, domain-specific annotated data is an invaluable resource for training effective models. However, in the medical domain, this data often includes P…
In-Context Learning on a Budget: A Case Study in Token Classification
Uri Berger, Tal Baumel, Gabriel Stanovsky
Few shot in-context learning (ICL) typically assumes access to large annotated training sets. However, in many real world scenarios, such as domain adaptation, there is only a limi…
Federated Multilingual Models for Medical Transcript Analysis
Andre Manoel, Mirian Hipolito Garcia, Tal Baumel +6
Federated Learning (FL) is a novel machine learning approach that allows the model trainer to access more data samples, by training the model across multiple decentralized data sou…
Question Answering as an Automatic Evaluation Metric for News Article Summarization
Matan Eyal, Tal Baumel, Michael Elhadad
Recent work in the field of automatic summarization and headline generation focuses on maximizing ROUGE scores for various news datasets. We present an alternative, extrinsic, eval…
Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Models
Tal Baumel, Matan Eyal, Michael Elhadad
Query Focused Summarization (QFS) has been addressed mostly using extractive methods. Such methods, however, produce text which suffers from low coherence. We investigate how abstr…
Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignment
Tal Baumel, Jumana Nassour-Kassis, Raphael Cohen +2
In the context of the Electronic Health Record, automated diagnosis coding of patient notes is a useful task, but a challenging one due to the large number of codes and the length…