---
title: "Who cites Jaewoo Kang — 1,417 papers of our library"
description: "1,417 papers of the Elamur Research library cite the works of Jaewoo Kang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jaewoo-kang/cited-by/"
---
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# Who cites Jaewoo Kang

1,446 citations of their works from 1,417 papers of our library (of the 141,840 whose bibliographies we read) · 88 with a page here, the most cited first · [← Jaewoo Kang](https://md.research.elamur.ai/free/en/authors/jaewoo-kang/)

1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,056 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
2. [**Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing arXiv:2007.15779**Yu Gu; Robert Tinn; Hao Cheng; Michael Lucas; Naoto Usuyama; Xiaodong Liu; Tristan Naumann; Jianfeng Gao;, Hoifung Poon*2020 · 2,655 citations*](https://md.research.elamur.ai/free/en/papers/gu-2020-domain-specific-language-model-pretraining/)
3. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,753 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
4. [**BERTopic: Neural topic modeling with a class-based TF-IDF procedure arXiv:2203.05794**Maarten Grootendorst*2022 · 1,732 citations*](https://md.research.elamur.ai/free/en/papers/grootendorst-2022-bertopic-neural-topic-modeling-class/)
5. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,648 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations* **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,549 citations* **[LEGAL-BERT: The Muppets straight out of Law School](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,493 citations* [**Publicly Available Clinical BERT Embeddings arXiv:1904.03323**Emily Alsentzer, John R. Murphy, Willie Boag, et al.*2019 · 1,226 citations*](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/) **[BERTweet: A pre-trained language model for English Tweets](https://md.research.elamur.ai/free/en/papers/nguyen-2020-bertweet-pre-trained-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen*2020 · 1,142 citations* **[Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets](https://md.research.elamur.ai/free/en/papers/peng-2019-transfer-learning-biomedical-natural-language/) [BioNLP Shared Task Workshop](https://md.research.elamur.ai/free/en/venues/bionlp-workshop-and-shared-task/)**Yifan Peng, Shankai Yan, Zhiyong Lu*2019 · 1,082 citations* **[A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,006 citations* [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arXiv:2304.13712**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 811 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) [**ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission arXiv:1904.05342**Kexin Huang, Jaan Altosaar, Rajesh Ranganath*2019 · 798 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/) **[CORD-19: The COVID-19 Open Research Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-cord-19-covid-19-open/) [Workshop on NLP for COVID-19 at EMNLP](https://md.research.elamur.ai/free/en/venues/nlpcovid19/)**Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al.*2020 · 689 citations* [**BloombergGPT: A Large Language Model for Finance arXiv:2303.17564**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 612 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/) [**Text Embeddings by Weakly-Supervised Contrastive Pre-training arXiv:2212.03533**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2022 · 594 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-text-embeddings-weakly-supervised-contrastive/) [**What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams arXiv:2009.13081**Di Jin, Eileen Pan, Nassim Oufattole, et al.*2020 · 546 citations*](https://md.research.elamur.ai/free/en/papers/jin-2020-disease-this-patient-have-large/) **[HateBERT: Retraining BERT for Abusive Language Detection in English](https://md.research.elamur.ai/free/en/papers/caselli-2021-hatebert-retraining-bert-abusive-language/) [Workshop on Online Abuse and Harms](https://md.research.elamur.ai/free/en/venues/woah/)**Tommaso Caselli, Valerio Basile, Jelena Mitrović, et al.*2021 · 481 citations* **[ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](https://md.research.elamur.ai/free/en/papers/santhanam-2022-colbertv2-effective-efficient-retrieval-lightweight/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.*2022 · 477 citations* **[LinkBERT: Pretraining Language Models with Document Links](https://md.research.elamur.ai/free/en/papers/yasunaga-2022-linkbert-pretraining-language-models-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michihiro Yasunaga, Jure Leskovec, Percy Liang*2022 · 456 citations* [**MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering arXiv:2203.14371 · ACM Conference on Health, Inference, and Learning (CHIL) 2022**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*2022 · 454 citations*](https://md.research.elamur.ai/free/en/papers/pal-2022-medmcqa-large-scale-multi-subject/) **[Large language models are few-shot clinical information extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-are-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 450 citations* **[Self-Alignment Pretraining for Biomedical Entity Representations](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al.*2021 · 434 citations* **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 426 citations* **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 408 citations* **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 400 citations* **[Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al.*2020 · 336 citations* **[Neural Unsupervised Domain Adaptation in NLP–-A Survey](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Alan Ramponi, Barbara Plank*2020 · 336 citations* **[Efficient Attentions for Long Document Summarization](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 335 citations* **[TimeLMs: Diachronic Language Models from Twitter](https://md.research.elamur.ai/free/en/papers/loureiro-2022-timelms-diachronic-language-models-twitter/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Loureiro, Francesco Barbieri, Leonardo Neves, et al.*2022 · 331 citations* **[Explainable Automated Fact-Checking for Public Health Claims](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Neema Kotonya, Francesca Toni*2020 · 314 citations* [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/) **[PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations* [**Multilingual is not enough: BERT for Finnish arXiv:1912.07076**Antti Virtanen, Jenna Kanerva, Rami Ilo, et al.*2019 · 258 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/) **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 245 citations* **[Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling](https://md.research.elamur.ai/free/en/papers/han-2019-unsupervised-domain-adaptation-contextualized-embeddings/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaochuang Han, Jacob Eisenstein*2019 · 242 citations* **[Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art](https://md.research.elamur.ai/free/en/papers/lewis-2020-pretrained-language-models-biomedical-clinical/) [Clinical Natural Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Patrick Lewis, Myle Ott, Jingfei Du, et al.*2020 · 241 citations* **[Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/shen-2021-locate-label-two-stage-identifier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongliang Shen, Xinyin Ma, Zeqi Tan, et al.*2021 · 231 citations* [**AlpaGasus: Training A Better Alpaca with Fewer Data arXiv:2307.08701**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 215 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/) **[Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning](https://md.research.elamur.ai/free/en/papers/wang-2021-improving-named-entity-recognition-external/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Wang, Yong Jiang, Nguyen Bach, et al.*2021 · 205 citations* **[CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters](https://md.research.elamur.ai/free/en/papers/boukkouri-2020-characterbert-reconciling-elmo-bert-word/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.*2020 · 204 citations* **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations* [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/) **[Re2G: Retrieve, Rerank, Generate](https://md.research.elamur.ai/free/en/papers/glass-2022-re2g-retrieve-rerank-generate/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.*2022 · 183 citations* **[Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again](https://md.research.elamur.ai/free/en/papers/gutierrez-2022-thinking-about-gpt-3-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bernal Jimenez Gutierrez, Nikolas McNeal, Clayton Washington, et al.*2022 · 179 citations* **[BillSum: A Corpus for Automatic Summarization of US Legislation](https://md.research.elamur.ai/free/en/papers/kornilova-2019-billsum-corpus-automatic-summarization-us/) [Workshop on New Frontiers in Summarization](https://md.research.elamur.ai/free/en/venues/workshop-on-new-frontiers-in-summarization/)**Anastassia Kornilova, Vladimir Eidelman*2019 · 175 citations* **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 168 citations* [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/) [**Lawyer LLaMA Technical Report arXiv:2305.15062**Quzhe Huang, Mingxu Tao, Chen Zhang, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lawyer-llama-technical-report/) **[Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks](https://md.research.elamur.ai/free/en/papers/mireshghallah-2022-quantifying-privacy-risks-masked-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, et al.*2022 · 145 citations* [**PMC-LLaMA: Towards Building Open-source Language Models for Medicine arXiv:2304.14454**Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-pmc-llama-towards-building-open/) **[Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation](https://md.research.elamur.ai/free/en/papers/ma-2021-zero-shot-neural-passage-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ji Ma, Ivan Korotkov, Yinfei Yang, et al.*2021 · 144 citations* [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges arXiv:2310.17631**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/) **[Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking](https://md.research.elamur.ai/free/en/papers/broscheit-2019-investigating-entity-knowledge-bert-simple/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Samuel Broscheit*2019 · 139 citations* **[Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains](https://md.research.elamur.ai/free/en/papers/shi-2019-next-sentence-prediction-helps-implicit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Shi, Vera Demberg*2019 · 134 citations* **[The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization](https://md.research.elamur.ai/free/en/papers/pilan-2022-text-anonymization-benchmark-tab-dedicated/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ildikó Pilán, Pierre Lison, Lilja Øvrelid, et al.*2022 · 129 citations* **[Evidence-based Fact-Checking of Health-related Claims](https://md.research.elamur.ai/free/en/papers/sarrouti-2021-evidence-based-fact-checking-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, et al.*2021 · 129 citations* **[Can Language Models be Biomedical Knowledge Bases?](https://md.research.elamur.ai/free/en/papers/sung-2021-can-language-models-be-biomedical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mujeen Sung, Jinhyuk Lee, Sean Yi, et al.*2021 · 127 citations* **[XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters](https://md.research.elamur.ai/free/en/papers/zhang-2023-xuanyuan-2-0-large-chinese/) [ACM International Conference on Information and Knowledge Management (CIKM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-information-and-knowledge-management-cikm/)**Xuanyu Zhang, Qing Yang, Dongliang Xu*2023 · 125 citations* [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/) [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities arXiv:2404.17790**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/) [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/) [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/) **[Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-large-language-models-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.*2025 · 75 citations* [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 72 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Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi*2020 · 68 citations* [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/) [**CMB: A Comprehensive Medical Benchmark in Chinese arXiv:2308.08833**Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-cmb-comprehensive-medical-benchmark/) **[Coreference Resolution for the Biomedical Domain: A Survey](https://md.research.elamur.ai/free/en/papers/lu-2021-coreference-resolution-biomedical-domain-survey/) [Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)](https://md.research.elamur.ai/free/en/venues/crac/)**Pengcheng Lu, Massimo Poesio*2021 · 17 citations* [**HeQ: a Large 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