{"total":98,"rows":[{"id":"2303.17564","title":"BloombergGPT: A Large Language Model for Finance","created":"2023-03-30","cited_by_count":939,"area":null},{"id":"2309.07430","title":"Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization","created":"2023-09-14","cited_by_count":246,"area":null},{"id":"2305.18703","title":"Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey","created":"2023-05-30","cited_by_count":135,"area":null},{"id":"2303.01229","title":"Almanac: Retrieval-Augmented Language Models for Clinical Medicine","created":"2023-03-01","cited_by_count":123,"area":"rag"},{"id":"2310.12321","title":"A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4","created":"2023-10-04","cited_by_count":81,"area":null},{"id":"2305.16326","title":"Benchmarking large language models for biomedical natural language processing applications and recommendations","created":"2023-05-10","cited_by_count":78,"area":null},{"id":"2306.12420","title":"LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models","created":"2023-06-21","cited_by_count":60,"area":null},{"id":"2308.06354","title":"Large Language Models to Identify Social Determinants of Health in Electronic Health Records","created":"2023-08-11","cited_by_count":55,"area":null},{"id":"2309.00237","title":"Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes","created":"2023-09-01","cited_by_count":51,"area":null},{"id":"2403.08002","title":"Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation","created":"2024-03-12","cited_by_count":51,"area":null},{"id":"2409.06857","title":"What is the Role of Small Models in the LLM Era: A Survey","created":"2024-09-10","cited_by_count":41,"area":null},{"id":"2307.03042","title":"Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain","created":"2023-07-06","cited_by_count":38,"area":null},{"id":"2303.12961","title":"The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs","created":"2023-03-22","cited_by_count":29,"area":null},{"id":"2411.04118","title":"Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?","created":"2024-11-06","cited_by_count":28,"area":"mllm"},{"id":"2310.19975","title":"BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing","created":"2023-10-30","cited_by_count":25,"area":null},{"id":"2411.09834","title":"A Benchmark for Long-Form Medical Question Answering","created":"2024-11-14","cited_by_count":25,"area":null},{"id":"2407.09429","title":"Open (Clinical) LLMs are Sensitive to Instruction Phrasings","created":"2024-07-12","cited_by_count":24,"area":null},{"id":"2403.07678","title":"MoralBERT: A Fine-Tuned Language Model for Capturing Moral Values in Social Discussions","created":"2024-03-12","cited_by_count":23,"area":null},{"id":"2403.05795","title":"ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes","created":"2024-03-09","cited_by_count":22,"area":null},{"id":"2311.00287","title":"Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models","created":"2023-11-01","cited_by_count":20,"area":null},{"id":"2406.19097","title":"Fairness and Bias in Multimodal AI: A Survey","created":"2024-06-27","cited_by_count":20,"area":"mllm"},{"id":"2305.11828","title":"Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews","created":"2023-05-19","cited_by_count":18,"area":null},{"id":"2402.12819","title":"Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance","created":"2024-02-20","cited_by_count":18,"area":null},{"id":"2304.02496","title":"Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification","created":"2023-04-05","cited_by_count":17,"area":"lr"},{"id":"2401.00579","title":"Exploring the Effectiveness of Instruction Tuning in Biomedical Language Processing","created":"2023-12-31","cited_by_count":16,"area":null},{"id":"2303.03948","title":"A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization","created":"2023-03-07","cited_by_count":14,"area":null},{"id":"2305.10284","title":"Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks","created":"2023-05-17","cited_by_count":14,"area":null},{"id":"2309.07438","title":"Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges","created":"2023-09-14","cited_by_count":14,"area":null},{"id":"2407.09241","title":"The Sociolinguistic Foundations of Language Modeling","created":"2024-07-12","cited_by_count":13,"area":null},{"id":"2404.07376","title":"LLMs in Biomedicine: A study on clinical Named Entity Recognition","created":"2024-04-10","cited_by_count":12,"area":null},{"id":"2504.19467","title":"BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text","created":"2025-04-28","cited_by_count":12,"area":null},{"id":"2306.05270","title":"Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes","created":"2023-06-08","cited_by_count":11,"area":null},{"id":"2307.02006","title":"PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records","created":"2023-07-05","cited_by_count":11,"area":null},{"id":"2403.11894","title":"From Explainable to Interpretable Deep Learning for Natural Language Processing in Healthcare: How Far from Reality?","created":"2024-03-18","cited_by_count":11,"area":null},{"id":"2305.10163","title":"Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries","created":"2023-05-17","cited_by_count":10,"area":null},{"id":"2405.00715","title":"Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation","created":"2024-04-25","cited_by_count":9,"area":null},{"id":"2405.01686","title":"Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models","created":"2024-05-02","cited_by_count":9,"area":null},{"id":"2306.05317","title":"CUED at ProbSum 2023: Hierarchical Ensemble of Summarization Models","created":"2023-06-08","cited_by_count":8,"area":null},{"id":"2306.14905","title":"PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Models","created":"2023-06-15","cited_by_count":8,"area":null},{"id":"2309.04550","title":"Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges","created":"2023-09-08","cited_by_count":8,"area":null},{"id":"2407.18525","title":"ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks","created":"2024-07-26","cited_by_count":8,"area":null},{"id":"2408.02600","title":"BioMamba: Domain-Adaptive Biomedical Language Models","created":"2024-08-05","cited_by_count":8,"area":null},{"id":"2306.15550","title":"CamemBERT-bio: Leveraging Continual Pre-training for Cost-Effective Models on French Biomedical Data","created":"2023-06-27","cited_by_count":7,"area":null},{"id":"2307.15425","title":"A Critical Review of Large Language Models: Sensitivity, Bias, and the Path Toward Specialized AI","created":"2023-07-28","cited_by_count":7,"area":null},{"id":"2310.08759","title":"Question Answering for Electronic Health Records: A Scoping Review of datasets and models","created":"2023-10-12","cited_by_count":7,"area":null},{"id":"2407.17638","title":"Time Matters: Examine Temporal Effects on Biomedical Language Models","created":"2024-07-24","cited_by_count":7,"area":null},{"id":"2504.20609","title":"WenyanGPT: A Large Language Model for Classical Chinese Tasks","created":"2025-04-29","cited_by_count":6,"area":null},{"id":"2412.10848","title":"Large Language Models for Medical Forecasting -- Foresight 2","created":"2024-12-14","cited_by_count":5,"area":null},{"id":"2306.02077","title":"Utilizing ChatGPT to Enhance Clinical Trial Enrollment","created":"2023-06-03","cited_by_count":4,"area":null},{"id":"2310.13998","title":"Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models","created":"2023-10-21","cited_by_count":4,"area":null},{"id":"2402.10597","title":"Efficiency at Scale: Investigating the Performance of Diminutive Language Models in Clinical Tasks","created":"2024-02-16","cited_by_count":4,"area":null},{"id":"2404.15549","title":"PRISM: Patient Records Interpretation for Semantic Clinical Trial Matching using Large Language Models","created":"2024-04-23","cited_by_count":4,"area":null},{"id":"2406.18094","title":"Shimo Lab at \"Discharge Me!\": Discharge Summarization by Prompt-Driven Concatenation of Electronic Health Record Sections","created":"2024-06-26","cited_by_count":4,"area":null},{"id":"2506.02306","title":"CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation","created":"2025-06-02","cited_by_count":4,"area":null},{"id":"2311.11211","title":"Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness","created":"2023-11-19","cited_by_count":3,"area":null},{"id":"2312.09469","title":"Clinical Text Deduplication Practices for Efficient Pretraining and Improved Clinical Tasks","created":"2023-09-29","cited_by_count":3,"area":null},{"id":"2408.01214","title":"High-Throughput Phenotyping of Clinical Text Using Large Language Models","created":"2024-08-02","cited_by_count":3,"area":null},{"id":"2412.05845","title":"Are Clinical T5 Models Better for Clinical Text?","created":"2024-12-08","cited_by_count":3,"area":null},{"id":"2503.01159","title":"Large Language Models for Healthcare Text Classification: A Systematic Review","created":"2025-03-03","cited_by_count":3,"area":null},{"id":"2510.16194","title":"Towards Automatic Evaluation and Selection of PHI De-identification Models via Multi-Agent Collaboration","created":"2025-10-17","cited_by_count":3,"area":"agents"},{"id":"2510.17892","title":"Advances in Pre-trained Language Models for Domain-Specific Text Classification: A Systematic Review","created":"2025-10-18","cited_by_count":3,"area":null},{"id":"2303.09366","title":"The Scope of In-Context Learning for the Extraction of Medical Temporal Constraints","created":"2023-03-16","cited_by_count":2,"area":null},{"id":"2308.09892","title":"Utilizing Semantic Textual Similarity for Clinical Survey Data Feature Selection","created":"2023-08-19","cited_by_count":2,"area":null},{"id":"2311.06121","title":"Multilingual and Multi-topical Benchmark of Fine-tuned Language models and Large Language Models for Check-Worthy Claim Detection","created":"2023-11-10","cited_by_count":2,"area":null},{"id":"2403.13112","title":"Efficient Encoder-Decoder Transformer Decoding for Decomposable Tasks","created":"2024-03-19","cited_by_count":2,"area":null},{"id":"2403.19511","title":"Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data","created":"2024-03-28","cited_by_count":2,"area":null},{"id":"2404.00484","title":"Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4","created":"2024-03-30","cited_by_count":2,"area":null},{"id":"2406.16611","title":"Evaluation of Language Models in the Medical Context Under Resource-Constrained Settings","created":"2024-06-24","cited_by_count":2,"area":null},{"id":"2407.19118","title":"Large Language Models as Co-Pilots for Causal Inference in Medical Studies","created":"2024-07-26","cited_by_count":2,"area":null},{"id":"2411.18940","title":"Rephrasing Electronic Health Records for Pretraining Clinical Language Models","created":"2024-11-28","cited_by_count":2,"area":null},{"id":"2507.03001","title":"Evaluating Hierarchical Clinical Document Classification Using Reasoning-Based LLMs","created":"2025-07-02","cited_by_count":2,"area":"lr"},{"id":"2603.13266","title":"Multi-hop Reasoning and Retrieval in Embedding Space: Leveraging Large Language Models with Knowledge","created":"2026-02-25","cited_by_count":2,"area":"lr"},{"id":"2605.01417","title":"Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks","created":"2026-05-02","cited_by_count":2,"area":null},{"id":"2306.09544","title":"Building blocks for complex tasks: Robust generative event extraction for radiology reports under domain shifts","created":"2023-06-15","cited_by_count":1,"area":null},{"id":"2311.08687","title":"An Eye on Clinical BERT: Investigating Language Model Generalization for Diabetic Eye Disease Phenotyping","created":"2023-11-15","cited_by_count":1,"area":null},{"id":"2312.03077","title":"Clinical Notes Reveal Physician Fatigue","created":"2023-12-05","cited_by_count":1,"area":null},{"id":"2312.13533","title":"Automated Clinical Coding for Outpatient Departments","created":"2023-12-21","cited_by_count":1,"area":null},{"id":"2402.10527","title":"Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks","created":"2024-02-16","cited_by_count":1,"area":null},{"id":"2406.14500","title":"Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2502.12584","title":"Enhancing Semi-supervised Learning with Zero-shot Pseudolabels","created":"2025-02-18","cited_by_count":1,"area":null},{"id":"2502.14189","title":"QUAD-LLM-MLTC: Large Language Models Ensemble Learning for Healthcare Text Multi-Label Classification","created":"2025-02-20","cited_by_count":1,"area":null},{"id":"2601.10167","title":"Credit C-GPT: A Domain-Specialized Large Language Model for Conversational Understanding in Vietnamese Debt Collection","created":"2026-01-15","cited_by_count":1,"area":null},{"id":"2604.23267","title":"Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective","created":"2026-04-25","cited_by_count":1,"area":null},{"id":"2309.12339","title":"Considerations for health care institutions training large language models on electronic health records","created":"2023-08-24","cited_by_count":0,"area":null},{"id":"2310.14358","title":"Right, No Matter Why: AI Fact-checking and AI Authority in Health-related Inquiry Settings","created":"2023-10-22","cited_by_count":0,"area":null},{"id":"2401.15222","title":"Transfer Learning for the Prediction of Entity Modifiers in Clinical Text: Application to Opioid Use Disorder Case Detection","created":"2024-01-26","cited_by_count":0,"area":null},{"id":"2409.10570","title":"Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking","created":"2024-09-14","cited_by_count":0,"area":"safety"},{"id":"2412.14387","title":"Clinical Trials Ontology Engineering with Large Language Models","created":"2024-12-18","cited_by_count":0,"area":null},{"id":"2503.04478","title":"Semantic Alignment of Unimodal Medical Text and Vision Representations","created":"2025-03-06","cited_by_count":0,"area":null},{"id":"2505.11810","title":"Efficiently Building a Domain-Specific Large Language Model from Scratch: A Case Study of a Classical Chinese Large Language Model","created":"2025-05-17","cited_by_count":0,"area":null},{"id":"2505.24767","title":"A survey of using EHR as real-world evidence for discovering and validating new drug indications","created":"2025-05-30","cited_by_count":0,"area":null},{"id":"2601.03423","title":"Training-Free Adaptation of New-Generation LLMs using Legacy Clinical Models","created":"2026-01-06","cited_by_count":0,"area":null},{"id":"2604.01727","title":"MATA-Former & SIICU: Semantic Aware Temporal Alignment for High-Fidelity ICU Risk Prediction","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2604.07116","title":"Yale-DM-Lab at ArchEHR-QA 2026: Deterministic Grounding and Multi-Pass Evidence Alignment for EHR Question Answering","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2606.21885","title":"Cohort-Anchored Foundation Models for Electronic Health Records: From Risk Scores to Auditable Peer Cohorts","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2609.26034","title":"Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.31629","title":"ChestPheNoT: Deployable, Auditable Label-Status-Evidence Extraction from Radiology Reports","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.36392","title":"ARCagent: An Adaptive Retrieval Calibration Agent for Clinical Question Answering","created":"2026-09-28","cited_by_count":0,"area":"rag"}],"next_cursor":null}