372 citations · 1.3k across the 15 of their papers we have counts for
9 papers · 1 filter
Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning
Yin Fang, Qiao Jin, Guangzhi Xiong +6
Cell type annotation is a key task in analyzing the heterogeneity of single-cell RNA sequencing data. Although recent foundation models automate this process, they typically annota…
Matching Patients to Clinical Trials with Large Language Models
Qiao Jin, Zifeng Wang, Charalampos S. Floudas +7
Patient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT…
GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information
Qiao Jin, Yifan Yang, Qingyu Chen +1
While large language models (LLMs) have been successfully applied to various tasks, they still face challenges with hallucinations. Augmenting LLMs with domain-specific tools such…
PMC-Patients: A Large-scale Dataset of Patient Summaries and Relations for Benchmarking Retrieval-based Clinical Decision Support Systems
Zhengyun Zhao, Qiao Jin, Fangyuan Chen +2
Objective: Retrieval-based Clinical Decision Support (ReCDS) can aid clinical workflow by providing relevant literature and similar patients for a given patient. However, the devel…
Biomedical Question Answering: A Survey of Approaches and Challenges
Qiao Jin, Zheng Yuan, Guangzhi Xiong +7
Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables innovat…
PubMedQA: A Dataset for Biomedical Research Question Answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu +2
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts. The task of PubMedQA is to answer research questions with yes/no/maybe (e…
Deep Contextualized Biomedical Abbreviation Expansion
Qiao Jin, Jinling Liu, Xinghua Lu
Automatic identification and expansion of ambiguous abbreviations are essential for biomedical natural language processing applications, such as information retrieval and question…
Probing Biomedical Embeddings from Language Models
Qiao Jin, Bhuwan Dhingra, William W. Cohen +1
Contextualized word embeddings derived from pre-trained language models (LMs) show significant improvements on downstream NLP tasks. Pre-training on domain-specific corpora, such a…
Neural Models for Reasoning over Multiple Mentions using Coreference
Bhuwan Dhingra, Qiao Jin, Zhilin Yang +2
Many problems in NLP require aggregating information from multiple mentions of the same entity which may be far apart in the text. Existing Recurrent Neural Network (RNN) layers ar…