5 citations · 11 across the 15 of their papers we have counts for
7 papers · 1 filter
MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering
Rezarta Islamaj, Robert Leaman, Joey Chan +13
Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain discriminative as model capabil…
ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?
Joey Chan, Yikun Han, Jingyuan Chen +8
Plain Language Summaries (PLS) aim to make research accessible to lay readers, but they are typically written in a one-size-fits-all style that ignores differences in readers' info…
Write Summary Step-by-Step: A Pilot Study of Stepwise Summarization
Xiuying Chen, Shen Gao, Mingzhe Li +3
Nowadays, neural text generation has made tremendous progress in abstractive summarization tasks. However, most of the existing summarization models take in the whole document all…
Flexible and Adaptable Summarization via Expertise Separation
Xiuying Chen, Mingzhe Li, Shen Gao +5
A proficient summarization model should exhibit both flexibility -- the capacity to handle a range of in-domain summarization tasks, and adaptability -- the competence to acquire n…
AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning
Qiao Jin, Zhizheng Wang, Yifan Yang +8
Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilizat…
Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports
Qingqing Zhu, Xiuying Chen, Qiao Jin +6
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics,…
Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark
Xiuying Chen, Tairan Wang, Qingqing Zhu +5
The summarization capabilities of pretrained and large language models (LLMs) have been widely validated in general areas, but their use in scientific corpus, which involves comple…