---
title: "Who cites Erik Tjong Kim Sang"
description: "1,796 papers of the Elamur Research library cite the works of Erik Tjong Kim Sang, found in their bibliographies · page 1 of 2 · 1–100; the most cited…"
canonical: "https://research.elamur.ai/free/en/authors/erik-tjong-kim-sang/cited-by/"
---
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# Who cites Erik Tjong Kim Sang

1,916 citations of their works from 1,796 papers of our library (of the 140,884 whose bibliographies we read) · 135 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Erik Tjong Kim Sang](https://md.research.elamur.ai/free/en/authors/erik-tjong-kim-sang/)

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1. [**BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding**Jacob Devlin, Ming-Wei Chang, Kenton Lee, et al.*2019 · 23,422 citations*](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/)
2. [**GloVe: Global Vectors for Word Representation**Jeffrey Pennington, Richard Socher, Christopher Manning*2014 · 5,962 citations*](https://md.research.elamur.ai/free/en/papers/pennington-2014-glove-global-vectors-word-representation/)
3. [**Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,375 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/)
4. [**Deep Contextualized Word Representations**Matthew E. Peters, Mark Neumann, Mohit Iyyer, et al.*2018 · 3,240 citations*](https://md.research.elamur.ai/free/en/papers/peters-2018-deep-contextualized-word-representations/)
5. [**The Proposition Bank: An Annotated Corpus of Semantic Roles**Martha Palmer, Daniel Gildea, Paul Kingsbury*2005 · 3,208 citations*](https://md.research.elamur.ai/free/en/papers/palmer-2005-proposition-bank-annotated-corpus-semantic/)
6. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
7. [**Stanza: A Python Natural Language Processing Toolkit for Many Human Languages**Peng Qi, Yuhao Zhang, Yuhui Zhang, et al.*2020 · 2,347 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-stanza-python-natural-language-processing/)
8. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
9. [**Design Challenges and Misconceptions in Named Entity Recognition**Lev Ratinov, Dan Roth*2009 · 1,836 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
10. [**What Does BERT Learn about the Structure of Language?**Ganesh Jawahar, Benoît Sagot, Djamé Seddah*2019 · 1,789 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2019-what-does-bert-learn-about/)
11. [**Named Entity Recognition in Tweets: An Experimental Study**Alan Ritter, Sam Clark, Mausam, et al.*2011 · 1,451 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-named-entity-recognition-tweets-experimental/)
12. [**Contextual String Embeddings for Sequence Labeling**Alan Akbik, Duncan Blythe, Roland Vollgraf*2018 · 1,390 citations*](https://md.research.elamur.ai/free/en/papers/akbik-2018-contextual-string-embeddings-sequence-labeling/)
13. [**brat: a Web-based Tool for NLP-Assisted Text Annotation**Pontus Stenetorp, Sampo Pyysalo, Goran Topić, et al.*2012 · 1,368 citations*](https://md.research.elamur.ai/free/en/papers/stenetorp-2012-brat-web-based-tool-nlp/)
14. [**DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing**Pengcheng He, Jianfeng Gao, Weizhu Chen*2021 · 1,316 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/)
15. [**AraBERT: Transformer-based Model for Arabic Language Understanding**Wissam Antoun, Fady Baly, Hazem Hajj*2020 · 1,297 citations*](https://md.research.elamur.ai/free/en/papers/antoun-2020-arabert-transformer-based-model-arabic/)
16. [**PIQA: Reasoning about Physical Commonsense in Natural Language**Yonatan Bisk, Rowan Zellers, Ronan Le Bras, et al.*2019 · 1,218 citations*](https://md.research.elamur.ai/free/en/papers/bisk-2019-piqa-reasoning-about-physical-commonsense/)
17. [**MASS: Masked Sequence to Sequence Pre-training for Language Generation**Kaitao Song, Xu Tan, Tao Qin, et al.*2019 · 1,109 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/)
18. [**Neural Architectures for Named Entity Recognition**Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, et al.*2016 · 1,021 citations*](https://md.research.elamur.ai/free/en/papers/lample-2016-neural-architectures-named-entity-recognition/)
19. [**P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks**Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.*2022 · 1,013 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-p-tuning-prompt-tuning-can/)
20. [**Linguistic Knowledge and Transferability of Contextual Representations**Nelson F. Liu, Matt Gardner, Yonatan Belinkov, et al.*2019 · 1,011 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-linguistic-knowledge-transferability-contextual-representations/)
21. [**Dependency Tree Kernels for Relation Extraction**Aron Culotta, Jeffrey Sorensen*2004 · 998 citations*](https://md.research.elamur.ai/free/en/papers/culotta-2004-dependency-tree-kernels-relation-extraction/)
22. [**ERNIE 2.0: A Continual Pre-training Framework for Language Understanding**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 976 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-2-0-continual/)
23. [**Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling**Xavier Carreras, Lluís Màrquez*2005 · 899 citations*](https://md.research.elamur.ai/free/en/papers/carreras-2005-introduction-conll-2005-shared-task/)
24. [**End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF**Xuezhe Ma, Eduard Hovy*2016 · 852 citations*](https://md.research.elamur.ai/free/en/papers/ma-2016-end-end-sequence-labeling-bi/)
25. [**A Unified MRC Framework for Named Entity Recognition**Xiaoya Li, Jingrong Feng, Yuxian Meng, et al.*2020 · 833 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-unified-mrc-framework-named-entity/)
26. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
27. [**Entity, Relation, and Event Extraction with Contextualized Span Representations**David Wadden, Ulme Wennberg, Yi Luan, et al.*2019 · 818 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2019-entity-relation-event-extraction-contextualized/)
28. [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/)
29. [**Named Entity Recognition using an HMM-based Chunk Tagger**GuoDong Zhou, Jian Su*2002 · 794 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2002-named-entity-recognition-hmm-based/)
30. [**Semi-supervised sequence tagging with bidirectional language models**Matthew E. Peters, Waleed Ammar, Chandra Bhagavatula, et al.*2017 · 786 citations*](https://md.research.elamur.ai/free/en/papers/peters-2017-semi-supervised-sequence-tagging-bidirectional/)
31. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
32. [**SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability**Eneko Agirre, Carmen Banea, Claire Cardie, et al.*2015 · 758 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2015-semeval-2015-task-2-semantic/)
33. [**Dice Loss for Data-imbalanced NLP Tasks**Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al.*2020 · 734 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-dice-loss-data-imbalanced-nlp/)
34. [**Introduction to the Bio-entity Recognition Task at JNLPBA**Nigel Collier, Tomoko Ohta, Yoshimasa Tsuruoka, et al.*2004 · 731 citations*](https://md.research.elamur.ai/free/en/papers/collier-2004-introduction-bio-entity-recognition-task/)
35. [**The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies**Mihai Surdeanu, Richard Johansson, Adam Meyers, et al.*2008 · 728 citations*](https://md.research.elamur.ai/free/en/papers/surdeanu-2008-conll-2008-shared-task-joint/)
36. [**KILT: a Benchmark for Knowledge Intensive Language Tasks**Fabio Petroni, Aleksandra Piktus, Angela Fan, et al.*2020 · 663 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-kilt-benchmark-knowledge-intensive-language/)
37. [**Chunking with Support Vector Machines**Taku Kudo, Yuji Matsumoto*2001 · 647 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2001-chunking-support-vector-machines/)
38. [**FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP**Alan Akbik, Tanja Bergmann, Duncan Blythe, et al.*2019 · 645 citations*](https://md.research.elamur.ai/free/en/papers/akbik-2019-flair-easy-use-framework-state/)
39. [**A Linear Programming Formulation for Global Inference in Natural Language Tasks**Dan Roth, Wen-tau Yih*2004 · 636 citations*](https://md.research.elamur.ai/free/en/papers/roth-2004-linear-programming-formulation-global-inference/)
40. [**A Frustratingly Easy Approach for Entity and Relation Extraction**Zexuan Zhong, Danqi Chen*2020 · 629 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-frustratingly-easy-approach-entity-relation/)
41. [**Harnessing Deep Neural Networks with Logic Rules**Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, et al.*2016 · 619 citations*](https://md.research.elamur.ai/free/en/papers/hu-2016-harnessing-deep-neural-networks-logic/)
42. [**BloombergGPT: A Large Language Model for Finance**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 608 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/)
43. [**Named Entity Recognition as Dependency Parsing**Juntao Yu, Bernd Bohnet, Massimo Poesio*2020 · 594 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-named-entity-recognition-as-dependency/)
44. [**Dissecting Contextual Word Embeddings: Architecture and Representation**Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, et al.*2018 · 585 citations*](https://md.research.elamur.ai/free/en/papers/peters-2018-dissecting-contextual-word-embeddings-architecture/)
45. [**A Survey on Recent Advances in Named Entity Recognition from Deep Learning models**Vikas Yadav, Steven Bethard*2018 · 565 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2018-survey-recent-advances-named-entity/)
46. [**Fast and Accurate Entity Recognition with Iterated Dilated Convolutions**Emma Strubell, Patrick Verga, David Belanger, et al.*2017 · 544 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2017-fast-accurate-entity-recognition-iterated/)
47. [**The Importance of Syntactic Parsing and Inference in Semantic Role Labeling**Vasin Punyakanok, Dan Roth, Wen-tau Yih*2008 · 538 citations*](https://md.research.elamur.ai/free/en/papers/punyakanok-2008-importance-syntactic-parsing-inference-semantic/)
48. [**Semi-Supervised Sequence Modeling with Cross-View Training**Kevin Clark, Minh-Thang Luong, Christopher D. Manning, et al.*2018 · 489 citations*](https://md.research.elamur.ai/free/en/papers/clark-2018-semi-supervised-sequence-modeling-cross/)
49. [**Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT**Shijie Wu, Mark Dredze*2019 · 466 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-beto-bentz-becas-surprising-cross/)
50. [**P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks**Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.*2021 · 464 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-p-tuning-v2-prompt-tuning/)
51. [**GPT-NER: Named Entity Recognition via Large Language Models**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/)
52. [**Recognizing Named Entities in Tweets**Xiaohua Liu, Shaodian Zhang, Furu Wei, et al.*2011 · 435 citations*](https://md.research.elamur.ai/free/en/papers/liu-2011-recognizing-named-entities-tweets/)
53. [**Template-Based Named Entity Recognition Using BART**Leyang Cui, Yu Wu, Jian Liu, et al.*2021 · 420 citations*](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/)
54. [**Empower Sequence Labeling with Task-Aware Neural Language Model**Liyuan Liu, Jingbo Shang, Frank F. Xu, et al.*2017 · 419 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-empower-sequence-labeling-task-aware/)
55. [**Nested Named Entity Recognition**Jenny Rose Finkel, Christopher D. Manning*2009 · 403 citations*](https://md.research.elamur.ai/free/en/papers/finkel-2009-nested-named-entity-recognition/)
56. [**Neural Architectures for Nested NER through Linearization**Jana Straková, Milan Straka, Jan Hajic*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/strakova-2019-neural-architectures-nested-ner-through/)
57. [**Entity Disambiguation for Knowledge Base Population**Mark Dredze, Paul McNamee, Delip Rao, et al.*2010 · 394 citations*](https://md.research.elamur.ai/free/en/papers/dredze-2010-entity-disambiguation-knowledge-base-population/)
58. [**A Unified Generative Framework for Various NER Subtasks**Hang Yan, Tao Gui, Junqi Dai, et al.*2021 · 392 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-various-ner/)
59. [**Sentence Simplification by Monolingual Machine Translation**Sander Wubben, Antal van den Bosch, Emiel Krahmer*2012 · 391 citations*](https://md.research.elamur.ai/free/en/papers/wubben-2012-sentence-simplification-monolingual-machine-translation/)
60. [**Pooled Contextualized Embeddings for Named Entity Recognition**Alan Akbik, Tanja Bergmann, Roland Vollgraf*2019 · 385 citations*](https://md.research.elamur.ai/free/en/papers/akbik-2019-pooled-contextualized-embeddings-named-entity/)
61. [**LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models**Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li*2023 · 379 citations*](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/)
62. [**Fine-Grained Analysis of Propaganda in News Articles**Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al.*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/)
63. [**Emerging Cross-lingual Structure in Pretrained Language Models**Alexis Conneau, Shijie Wu, Haoran Li, et al.*2020 · 378 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/)
64. [**An Analysis of Encoder Representations in Transformer-Based Machine Translation**Alessandro Raganato, Jörg Tiedemann*2018 · 366 citations*](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/)
65. [**Datasets: A Community Library for Natural Language Processing**Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, et al.*2021 · 358 citations*](https://md.research.elamur.ai/free/en/papers/lhoest-2021-datasets-community-library-natural-language/)
66. [**XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation**Yaobo Liang, Nan Duan, Yeyun Gong, et al.*2020 · 356 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/)
67. [**Cross-lingual Word Clusters for Direct Transfer of Linguistic Structure**Oscar Täckström, Ryan McDonald, Jakob Uszkoreit*2012 · 340 citations*](https://md.research.elamur.ai/free/en/papers/tackstrom-2012-cross-lingual-word-clusters-direct/)
68. [**Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings**Thomas Manzini, Lim Yao Chong, Alan W Black, et al.*2019 · 332 citations*](https://md.research.elamur.ai/free/en/papers/manzini-2019-black-is-criminal-as-caucasian/)
69. [**Massively Multilingual Transfer for NER**Afshin Rahimi, Yuan Li, Trevor Cohn*2019 · 328 citations*](https://md.research.elamur.ai/free/en/papers/rahimi-2019-massively-multilingual-transfer-ner/)
70. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 324 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
71. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 322 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
72. [**The Necessity of Parsing for Predicate Argument Recognition**Daniel Gildea, Martha Palmer*2002 · 293 citations*](https://md.research.elamur.ai/free/en/papers/gildea-2002-necessity-parsing-predicate-argument-recognition/)
73. [**Shared Tasks of the 2015 Workshop on Noisy User-generated Text: Twitter Lexical Normalization and Named Entity Recognition**Timothy Baldwin, Marie Catherine de Marneffe, Bo Han, et al.*2015 · 287 citations*](https://md.research.elamur.ai/free/en/papers/baldwin-2015-shared-tasks-2015-workshop-noisy/)
74. [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**Jue Wang, Wei Lu*2020 · 286 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/)
75. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT**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 · 272 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
76. [**Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network**Yutai Hou, Wanxiang Che, Yongkui Lai, et al.*2020 · 265 citations*](https://md.research.elamur.ai/free/en/papers/hou-2020-few-shot-slot-tagging-collapsed/)
77. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
78. [**NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 245 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/)
79. [**Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling**Xiaochuang Han, Jacob Eisenstein*2019 · 242 citations*](https://md.research.elamur.ai/free/en/papers/han-2019-unsupervised-domain-adaptation-contextualized-embeddings/)
80. [**CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning**Sarkar Snigdha Sarathi Das, Arzoo Katiyar, Rebecca Passonneau, et al.*2022 · 233 citations*](https://md.research.elamur.ai/free/en/papers/das-2022-container-few-shot-named-entity/)
81. [**Putting it Simply: a Context-Aware Approach to Lexical Simplification**Or Biran, Samuel Brody, Noémie Elhadad*2011 · 222 citations*](https://md.research.elamur.ai/free/en/papers/biran-2011-putting-it-simply-context-aware/)
82. [**Open-Source Tools for Morphology, Lemmatization, POS Tagging and Named Entity Recognition**Jana Straková, Milan Straka, Jan Hajič*2014 · 217 citations*](https://md.research.elamur.ai/free/en/papers/strakova-2014-open-source-tools-morphology-lemmatization/)
83. [**Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/)
84. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 209 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/)
85. [**A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/)
86. [**Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning**Jesujoba O. Alabi, David Ifeoluwa Adelani, Marius Mosbach, et al.*2022 · 195 citations*](https://md.research.elamur.ai/free/en/papers/alabi-2022-adapting-pre-trained-language-models/)
87. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
88. [**Time-Aware Language Models as Temporal Knowledge Bases**Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, et al.*2022 · 194 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2022-time-aware-language-models-as/)
89. [**Exploring and Predicting Transferability across NLP Tasks**Tu Vu, Tong Wang, Tsendsuren Munkhdalai, et al.*2020 · 192 citations*](https://md.research.elamur.ai/free/en/papers/vu-2020-exploring-predicting-transferability-across-nlp/)
90. [**Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation**Adam Poliak, Aparajita Haldar, Rachel Rudinger, et al.*2018 · 190 citations*](https://md.research.elamur.ai/free/en/papers/poliak-2018-collecting-diverse-natural-language-inference/)
91. [**GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/)
92. [**DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension**Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra, et al.*2018 · 188 citations*](https://md.research.elamur.ai/free/en/papers/saha-2018-duorc-complex-language-understanding-paraphrased/)
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