---
title: "Who cites Monica Agrawal — 202 papers of our library"
description: "202 papers of the Elamur Research library cite the works of Monica Agrawal, found in their bibliographies; the most cited first."
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---
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# Who cites Monica Agrawal

205 citations of their works from 202 papers of our library (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · [← Monica Agrawal](https://md.research.elamur.ai/free/en/authors/monica-agrawal/)

1. **[Large Language Models Encode Clinical Knowledge](https://md.research.elamur.ai/free/en/papers/singhal-2022-large-language-models-encode-clinical/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Karan Singhal, Shekoofeh Azizi, Tao Tu, et al.*2022 · 4,492 citations*
2. **[Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.*2022 · 754 citations*
3. **[Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree](https://md.research.elamur.ai/free/en/papers/sun-2019-aspect-level-sentiment-analysis-convolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kai Sun, Richong Zhang, Samuel Mensah, et al.*2019 · 499 citations*
4. **[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 · 454 citations*
5. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations*
6. **[Large Language Models are Few-Shot Clinical Information Extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-few-shot/) [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 · 384 citations*
7. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
8. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Qin, Rolf Jagerman, Kai Hui, et al.*2024 · 300 citations*
9. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT arXiv:2302.10205**Xiang Wei; Xingyu Cui; Ning Cheng; Xiaobin Wang; Xin Zhang; Shen Huang; Pengjun Xie; Jinan Xu; Yufeng Chen; Meishan Zhang; Yong Jiang;, Wenjuan Han*2023 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
10. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
11. **[Med-HALT: Medical Domain Hallucination Test for Large Language Models](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*2023 · 221 citations*
12. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 212 citations*
13. **[GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*
14. **[CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors](https://md.research.elamur.ai/free/en/papers/li-2023-codeie-large-code-generation-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peng Li, Tianxiang Sun, Qiong Tang, et al.*2023 · 109 citations*
15. **[Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes](https://md.research.elamur.ai/free/en/papers/arora-2023-language-models-enable-simple-systems/) [Proceedings of the VLDB Endowment](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-vldb-endowment/)**Simran Arora, Brandon Yang, Sabri Eyuboglu, et al.*2023 · 94 citations*
16. **[DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents](https://md.research.elamur.ai/free/en/papers/nair-2023-dera-enhancing-large-language-model/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Varun Nair, Elliot Schumacher, Geoffrey Tso, et al.*2023 · 55 citations*
17. [**Self-Verification Improves Few-Shot Clinical Information Extraction arXiv:2306.00024 · IMLH 2023**Zelalem Gero, Chandan Singh, Hao Cheng, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gero-2023-self-verification-improves-few-shot/)
18. [**PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions arXiv:2305.14908**Anthony Chen, Panupong Pasupat, Sameer Singh, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-purr-efficiently-editing-language-model/)
19. [**Are Large Language Models Robust Coreference Resolvers? arXiv:2305.14489**Nghia T. Le, Alan Ritter*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/le-2023-large-language-models-robust-coreference/)
20. **[Understanding the Dark Side of LLMs' Intrinsic Self-Correction](https://md.research.elamur.ai/free/en/papers/zhang-2025-understanding-dark-side-llms-intrinsic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingjie Zhang, Di Wang, Haoting Qian, et al.*2025 · 21 citations*
21. **[Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Experts](https://md.research.elamur.ai/free/en/papers/le-2022-few-shot-anaphora-resolution-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nghia T. Le, Fan Bai, Alan Ritter*2022 · 20 citations*
22. **[Major Entity Identification: A Generalizable Alternative to Coreference Resolution](https://md.research.elamur.ai/free/en/papers/manikantan-2024-major-entity-identification-generalizable-alternative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kawshik Manikantan, Shubham Toshniwal, Makarand Tapaswi, et al.*2024 · 13 citations*
23. **[Multilingual coreference resolution as text generation](https://md.research.elamur.ai/free/en/papers/skachkova-2024-multilingual-coreference-resolution-as-text/) [Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)](https://md.research.elamur.ai/free/en/venues/crac/)**Natalia Skachkova*2024 · 6 citations*
24. **[Attention to Non-Adopters](https://md.research.elamur.ai/free/en/papers/zhou-2026-attention-non-adopters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, et al.*2026 · 1 citation*
25. **[Gladiator at MEDIQA-SYNUR 2026: Contextual Clinical Extraction: Integrating Foundation Models with Domain-Specific Validation Rules](https://md.research.elamur.ai/free/en/papers/pusapati-2026-gladiator-mediqa-synur-2026-contextual/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Siva Satyanarayana Raju Pusapati, Ankit Singh*2026 · 1 citation*
26. **[HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive Content](https://md.research.elamur.ai/free/en/papers/vecchi-2026-harm-learning-hate-aware-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.*2026 · 1 citation*
27. **[HSE NLP TEAM at MEDIQA-SYNUR 2026: Consensus Adjudication Ensemble (ACE): Balancing Precision and Recall for Schema-Bystander Clinical Extraction](https://md.research.elamur.ai/free/en/papers/valiev-2026-hse-nlp-team-mediqa-synur/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Airat A. Valiev*2026 · 1 citation*
28. **[Smart_solutions at MEDIQA-SYNUR 2026: A Multi-Stage LLM Pipeline for Nursing Observation Extraction](https://md.research.elamur.ai/free/en/papers/munjal-2026-smart-solutions-mediqa-synur-2026/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Prateek Munjal*2026 · 1 citation*
29. **[A Herd of Language Models Makes a Better Zero-shot Annotator for Clinical Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/shimizu-2026-herd-language-models-makes-better/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seiji Shimizu, Shoko Wakamiya, Eiji Aramaki*2026*
30. **[EpiGator: An Event-based Surveillance System for Infectious Disease Outbreaks](https://md.research.elamur.ai/free/en/papers/wu-2026-epigator-event-based-surveillance-system/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yiheng Wu, Jue Hou, Trangcasanchai Sathianpong, et al.*2026*
31. **[Faithful Medical Dialogue Generation Using Homo-Heterogeneous Exemplar-based In-Context Knowledge Grounding](https://md.research.elamur.ai/free/en/papers/priya-2026-faithful-medical-dialogue-generation-homo/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Priyanshu Priya, Hardik Goyal, Asif Ekbal*2026*
32. **[Mask-to-Correct+: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction](https://md.research.elamur.ai/free/en/papers/santra-2026-mask-correct-leveraging-retriever-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Payel Santra, Lavisha Sharma, Madhusudan Ghosh, et al.*2026*
33. **[Mind Your Steps in Biomedical Named Entity Recognition: First Extract, Tag Afterwards](https://md.research.elamur.ai/free/en/papers/shlyk-2026-mind-your-steps-biomedical-named/) [Workshop on Linguistic Analysis for Health](https://md.research.elamur.ai/free/en/venues/healing/)**Darya Shlyk, Stefano Montanelli, Marco Mesiti, et al.*2026*
34. **[sebis at CRF Filling 2026: A Two-Stage Local LLM Pipeline for Medical CRF Filling](https://md.research.elamur.ai/free/en/papers/sommer-2026-sebis-crf-filling-2026-two/) [Workshop on Patient-Oriented Language Processing @ LREC](https://md.research.elamur.ai/free/en/venues/cl4health/)**Katharina Sommer, Tristan Till, Florian Matthes*2026*

168 more citing papers of our library have no page here yet.

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