Papers by Emma Lundberg

2 papers
Classifying Implant-Bearing Patients via their Medical Histories: a Pre-Study on Swedish EMRs with Semi-Supervised GanBERT (2022.lrec-1)

Copied to clipboard

Challenge: Identifying the presence of implants in certain patients is important for radiologists because some implants are not compatible with MRI scanning.
Approach: They compare the performance of two BERT-based text classifiers whose task is to classify patients as having or not having implant(s) in their body.
Outcome: The proposed classifiers outperform fully-supervised classifier models on annotated data.
PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR (2026.eacl-long)

Copied to clipboard

Challenge: Recent methods supervise only the final answer accuracy using reinforcement learning with verifiable rewards (RLVR).
Approach: They propose to train search agents to search and reason over scientific papers and a factoid QA dataset with 60k biomedical paper abstracts.
Outcome: The proposed model outperforms non-RL retrieval baselines and is scalable and extendable to other scientific domains.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations