most citedEvaluating the Zero-shot Robustness of Instruction-tuned Language Models

12 citations · 35 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2023★ 12 cited

Evaluating the Zero-shot Robustness of Instruction-tuned Language Models

Jiuding Sun, Chantal Shaib, Byron C. Wallace

Instruction fine-tuning has recently emerged as a promising approach for improving the zero-shot capabilities of Large Language Models (LLMs) on new tasks. This technique has shown…

cs.CL2023★ 3 cited

Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations

Lucy Lu Wang, Yulia Otmakhova, Jay DeYoung +4

Evaluating multi-document summarization (MDS) quality is difficult. This is especially true in the case of MDS for biomedical literature reviews, where models must synthesize contr…

cs.CL2023★ 4 cited

Summarizing, Simplifying, and Synthesizing Medical Evidence Using GPT-3 (with Varying Success)

Chantal Shaib, Millicent L. Li, Sebastian Joseph +3

Large language models, particularly GPT-3, are able to produce high quality summaries of general domain news articles in few- and zero-shot settings. However, it is unclear if such…

cs.CL2023★ 1 cited

Multilingual Simplification of Medical Texts

Sebastian Joseph, Kathryn Kazanas, Keziah Reina +4

Automated text simplification aims to produce simple versions of complex texts. This task is especially useful in the medical domain, where the latest medical findings are typicall…

cs.CL2023★ 3 cited

Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews

Hye Sun Yun, Iain J. Marshall, Thomas A. Trikalinos +1

Medical systematic reviews play a vital role in healthcare decision making and policy. However, their production is time-consuming, limiting the availability of high-quality and up…

cs.CL2023★ 9 cited

Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs

Somin Wadhwa, Jay DeYoung, Benjamin Nye +2

Results from Randomized Controlled Trials (RCTs) establish the comparative effectiveness of interventions, and are in turn critical inputs for evidence-based care. However, results…

cs.CL2023★ 1 cited

Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges

Sanjana Ramprasad, Denis Jered McInerney, Iain J. Marshal +1

We present TrialsSummarizer, a system that aims to automatically summarize evidence presented in the set of randomized controlled trials most relevant to a given query. Building on…

cs.LG2022

That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data

Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent +1

Pretraining multimodal models on Electronic Health Records (EHRs) provides a means of learning representations that can transfer to downstream tasks with minimal supervision. Recen…

cs.CL2022★ 2 cited

RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media

Somin Wadhwa, Vivek Khetan, Silvio Amir +1

We present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social media posts from Reddit spanning 24 health conditions. Annotations include demarcations of…