{"total":422,"rows":[{"id":"2303.17564","title":"BloombergGPT: A Large Language Model for Finance","created":"2023-03-30","cited_by_count":939,"area":null},{"id":"2111.01243","title":"Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey","created":"2021-11-01","cited_by_count":463,"area":null},{"id":"2307.15189","title":"Med-Flamingo: a Multimodal Medical Few-shot Learner","created":"2023-07-27","cited_by_count":392,"area":null},{"id":"2205.12628","title":"Are Large Pre-Trained Language Models Leaking Your Personal Information?","created":"2022-05-25","cited_by_count":200,"area":null},{"id":"2305.13523","title":"A Study of Generative Large Language Model for Medical Research and Healthcare","created":"2023-05-22","cited_by_count":163,"area":null},{"id":"2310.05694","title":"A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics","created":"2023-10-09","cited_by_count":163,"area":null},{"id":"2110.15621","title":"MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare","created":"2021-10-29","cited_by_count":161,"area":null},{"id":"2401.06775","title":"Large language models in healthcare and medical domain: A review","created":"2023-12-12","cited_by_count":127,"area":null},{"id":"2310.10196","title":"Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook","created":"2023-10-16","cited_by_count":110,"area":null},{"id":"2406.10833","title":"A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery","created":"2024-06-16","cited_by_count":96,"area":null},{"id":"2104.07762","title":"Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?","created":"2021-04-15","cited_by_count":93,"area":null},{"id":"2306.03030","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","created":"2023-06-05","cited_by_count":91,"area":null},{"id":"2110.05006","title":"Pre-trained Language Models in Biomedical Domain: A Systematic Survey","created":"2021-10-11","cited_by_count":87,"area":null},{"id":"2104.06486","title":"MS2: Multi-Document Summarization of Medical Studies","created":"2021-04-13","cited_by_count":80,"area":null},{"id":"2205.08514","title":"Recovering Private Text in Federated Learning of Language Models","created":"2022-05-17","cited_by_count":70,"area":null},{"id":"2201.11838","title":"Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences","created":"2022-01-27","cited_by_count":69,"area":null},{"id":"2307.15220","title":"Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures","created":"2023-07-27","cited_by_count":68,"area":null},{"id":"2306.02069","title":"MultiLegalPile: A 689GB Multilingual Legal Corpus","created":"2023-06-03","cited_by_count":60,"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":"2402.03182","title":"Empowering Time Series Analysis with Large Language Models: A Survey","created":"2024-02-05","cited_by_count":60,"area":null},{"id":"2406.10729","title":"A Comprehensive Survey of Foundation Models in Medicine","created":"2024-06-15","cited_by_count":56,"area":null},{"id":"2104.08116","title":"Temporal Adaptation of BERT and Performance on Downstream Document Classification: Insights from Social Media","created":"2021-04-16","cited_by_count":51,"area":null},{"id":"2205.00619","title":"POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection","created":"2022-05-02","cited_by_count":51,"area":null},{"id":"2102.04252","title":"HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data","created":"2021-02-08","cited_by_count":49,"area":null},{"id":"2308.06966","title":"EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce","created":"2023-08-14","cited_by_count":49,"area":null},{"id":"2207.11280","title":"PanGu-Coder: Program Synthesis with Function-Level Language Modeling","created":"2022-07-22","cited_by_count":48,"area":null},{"id":"2208.10240","title":"A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction","created":"2022-08-09","cited_by_count":48,"area":null},{"id":"2102.05281","title":"Biomedical Question Answering: A Survey of Approaches and Challenges","created":"2021-02-10","cited_by_count":46,"area":null},{"id":"2102.04110","title":"Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration","created":"2021-02-08","cited_by_count":44,"area":null},{"id":"2405.10075","title":"HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase Recognition","created":"2024-05-16","cited_by_count":42,"area":null},{"id":"2312.10251","title":"Advancing Surgical VQA with Scene Graph Knowledge","created":"2023-12-15","cited_by_count":41,"area":null},{"id":"2103.06511","title":"Does the Magic of BERT Apply to Medical Code Assignment? A Quantitative Study","created":"2021-03-11","cited_by_count":39,"area":null},{"id":"2410.00263","title":"Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation","created":"2024-09-30","cited_by_count":39,"area":null},{"id":"2106.07340","title":"MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education","created":"2021-06-02","cited_by_count":37,"area":null},{"id":"2203.15588","title":"Deep Multi-modal Fusion of Image and Non-image Data in Disease Diagnosis and Prognosis: A Review","created":"2022-03-25","cited_by_count":37,"area":null},{"id":"2107.02975","title":"Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review","created":"2021-07-07","cited_by_count":35,"area":null},{"id":"2301.11847","title":"A Comparative Study of Pretrained Language Models for Long Clinical Text","created":"2023-01-27","cited_by_count":35,"area":null},{"id":"2109.07460","title":"Efficient Domain Adaptation of Language Models via Adaptive Tokenization","created":"2021-09-15","cited_by_count":34,"area":null},{"id":"2206.14674","title":"Signature Methods in Machine Learning","created":"2022-06-29","cited_by_count":34,"area":null},{"id":"2306.05406","title":"Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models Memories","created":"2023-06-08","cited_by_count":34,"area":null},{"id":"2406.03712","title":"A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions","created":"2024-06-06","cited_by_count":34,"area":null},{"id":"2210.12156","title":"Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling","created":"2022-10-18","cited_by_count":33,"area":null},{"id":"2401.00434","title":"GeoGalactica: A Scientific Large Language Model in Geoscience","created":"2023-12-31","cited_by_count":33,"area":null},{"id":"2311.17330","title":"Biomedical knowledge graph-optimized prompt generation for large language models","created":"2023-11-29","cited_by_count":31,"area":null},{"id":"2309.12625","title":"DRG-LLaMA : Tuning LLaMA Model to Predict Diagnosis-related Group for Hospitalized Patients","created":"2023-09-22","cited_by_count":30,"area":null},{"id":"2304.00958","title":"DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains","created":"2023-04-03","cited_by_count":27,"area":null},{"id":"2110.15763","title":"How to Leverage Multimodal EHR Data for Better Medical Predictions?","created":"2021-10-29","cited_by_count":26,"area":null},{"id":"2201.02797","title":"A Unified Review of Deep Learning for Automated Medical Coding","created":"2022-01-08","cited_by_count":26,"area":null},{"id":"2401.06774","title":"Two Directions for Clinical Data Generation with Large Language Models: Data-to-Label and Label-to-Data","created":"2023-12-09","cited_by_count":26,"area":null},{"id":"2504.03964","title":"Clinical ModernBERT: An efficient and long context encoder for biomedical text","created":"2025-04-04","cited_by_count":26,"area":null},{"id":"2101.06426","title":"A Survey on Extraction of Causal Relations from Natural Language Text","created":"2021-01-16","cited_by_count":25,"area":null},{"id":"2203.09127","title":"ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps","created":"2022-03-17","cited_by_count":25,"area":null},{"id":"2108.08983","title":"SMedBERT: A Knowledge-Enhanced Pre-trained Language Model with Structured Semantics for Medical Text Mining","created":"2021-08-20","cited_by_count":24,"area":null},{"id":"2311.04937","title":"Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine","created":"2023-11-07","cited_by_count":24,"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":"2409.04481","title":"Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials","created":"2024-09-06","cited_by_count":24,"area":null},{"id":"2503.13709","title":"Multi-modal Time Series Analysis: A Tutorial and Survey","created":"2025-03-17","cited_by_count":24,"area":null},{"id":"2211.03154","title":"On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey","created":"2022-11-06","cited_by_count":23,"area":null},{"id":"2209.13136","title":"A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language Processing","created":"2022-09-27","cited_by_count":22,"area":null},{"id":"2402.00160","title":"Emergency Department Decision Support using Clinical Pseudo-notes","created":"2024-01-31","cited_by_count":22,"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":"2110.08173","title":"Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models","created":"2021-10-15","cited_by_count":21,"area":null},{"id":"2309.00087","title":"Large language models in medicine: the potentials and pitfalls","created":"2023-08-31","cited_by_count":21,"area":null},{"id":"2402.13253","title":"BiMediX: Bilingual Medical Mixture of Experts LLM","created":"2024-02-20","cited_by_count":21,"area":null},{"id":"2307.03067","title":"DeepOnto: A Python Package for Ontology Engineering with Deep Learning","created":"2023-07-06","cited_by_count":20,"area":null},{"id":"2403.10822","title":"Can Large Language Models abstract Medical Coded Language?","created":"2024-03-16","cited_by_count":20,"area":null},{"id":"2205.05535","title":"Clinical Prompt Learning with Frozen Language Models","created":"2022-05-11","cited_by_count":19,"area":null},{"id":"2307.11346","title":"CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Study","created":"2023-07-21","cited_by_count":19,"area":null},{"id":"2310.14088","title":"MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation","created":"2023-10-21","cited_by_count":19,"area":null},{"id":"2312.05256","title":"Holistic Evaluation of GPT-4V for Biomedical Imaging","created":"2023-11-10","cited_by_count":19,"area":null},{"id":"2408.02056","title":"MedSyn: LLM-based Synthetic Medical Text Generation Framework","created":"2024-08-04","cited_by_count":19,"area":null},{"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":"2309.04175","title":"Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese","created":"2023-09-08","cited_by_count":18,"area":null},{"id":"2204.13032","title":"BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information","created":"2022-04-27","cited_by_count":17,"area":null},{"id":"2307.00067","title":"Transformers in Healthcare: A Survey","created":"2023-06-30","cited_by_count":17,"area":null},{"id":"2405.19524","title":"AI Risk Management Should Incorporate Both Safety and Security","created":"2024-05-29","cited_by_count":17,"area":null},{"id":"2508.09874","title":"Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models","created":"2025-08-13","cited_by_count":16,"area":null},{"id":"2103.10928","title":"BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients","created":"2021-03-19","cited_by_count":15,"area":null},{"id":"2302.12343","title":"CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models","created":"2023-02-23","cited_by_count":15,"area":null},{"id":"2507.23276","title":"How Far Are AI Scientists from Changing the World?","created":"2025-07-31","cited_by_count":15,"area":null},{"id":"2110.15803","title":"Natural Language Processing for Smart Healthcare","created":"2021-10-19","cited_by_count":14,"area":null},{"id":"2203.14469","title":"Integrating Physiological Time Series and Clinical Notes with Transformer for Early Prediction of Sepsis","created":"2022-03-28","cited_by_count":14,"area":null},{"id":"2204.06766","title":"Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission","created":"2022-04-14","cited_by_count":14,"area":null},{"id":"2210.06277","title":"Task Compass: Scaling Multi-task Pre-training with Task Prefix","created":"2022-10-12","cited_by_count":14,"area":null},{"id":"2307.00186","title":"How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain","created":"2023-07-01","cited_by_count":14,"area":null},{"id":"2403.15401","title":"Large Language Model for Mental Health: A Systematic Review","created":"2024-02-19","cited_by_count":14,"area":null},{"id":"2408.04138","title":"Enhancing Healthcare through Large Language Models: A Study on Medical Question Answering","created":"2024-08-08","cited_by_count":14,"area":null},{"id":"2102.11573","title":"Automated Quality Assessment of Cognitive Behavioral Therapy Sessions Through Highly Contextualized Language Representations","created":"2021-02-23","cited_by_count":13,"area":null},{"id":"2201.10113","title":"Multimodal data matters: language model pre-training over structured and unstructured electronic health records","created":"2022-01-25","cited_by_count":13,"area":null},{"id":"2204.10716","title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","created":"2022-04-22","cited_by_count":13,"area":null},{"id":"2309.06828","title":"UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training","created":"2023-09-13","cited_by_count":13,"area":null},{"id":"2503.07667","title":"CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models","created":"2025-03-09","cited_by_count":13,"area":null},{"id":"2103.03125","title":"Advances in Multi-turn Dialogue Comprehension: A Survey","created":"2021-03-04","cited_by_count":12,"area":null},{"id":"2211.00430","title":"VarMAE: Pre-training of Variational Masked Autoencoder for Domain-adaptive Language Understanding","created":"2022-11-01","cited_by_count":12,"area":null},{"id":"2305.00237","title":"A Review of ChatGPT Applications in Education, Marketing, Software Engineering, and Healthcare: Benefits, Drawbacks, and Research Directions","created":"2023-04-29","cited_by_count":12,"area":null},{"id":"2405.06784","title":"Open Challenges and Opportunities in Federated Foundation Models Towards Biomedical Healthcare","created":"2024-05-10","cited_by_count":12,"area":null},{"id":"2109.01048","title":"Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation","created":"2021-09-02","cited_by_count":11,"area":null},{"id":"2109.04738","title":"On the validity of pre-trained transformers for natural language processing in the software engineering domain","created":"2021-09-10","cited_by_count":11,"area":null},{"id":"2302.12893","title":"Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation","created":"2023-02-24","cited_by_count":11,"area":null},{"id":"2305.13052","title":"Federated Learning of Medical Concepts Embedding using BEHRT","created":"2023-05-22","cited_by_count":11,"area":null}],"next_cursor":"100"}