---
title: "Who cites Fei Qing Wu — 1,360 papers of our library"
description: "1,360 papers of the Elamur Research library cite the works of Fei Qing Wu, found in their bibliographies · page 1 of 3 · 1–100; the most cited first."
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---
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# Who cites Fei Qing Wu

1,471 citations of their works from 1,360 papers of our library (of the 149,439 whose bibliographies we read) · 254 with a page here, the most cited first · page 1 of 3 · 1–100 · [← Fei Qing Wu](https://md.research.elamur.ai/free/en/authors/fei-qing-wu/)

**1** [2](https://md.research.elamur.ai/free/en/authors/fei-qing-wu/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/fei-qing-wu/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/authors/fei-qing-wu/cited-by/page/2/)

1. **[Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,423 citations*
2. [**Teaching Machines to Read and Comprehend arXiv:1506.03340**Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, et al.*2015 · 3,858 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2015-teaching-machines-read-comprehend/)
3. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
4. **[Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification](https://md.research.elamur.ai/free/en/papers/zhou-2016-attention-based-bidirectional-long-short/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peng Zhou, Wei Shi, Jun Tian, et al.*2016 · 2,219 citations*
5. [**Finetuned Language Models Are Zero-Shot Learners arXiv:2109.01652**Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.*2021 · 1,954 citations*](https://md.research.elamur.ai/free/en/papers/wei-2021-finetuned-language-models-zero-shot/)
6. **[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 · 1,556 citations*
7. **[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 · 1,551 citations*
8. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
9. **[Leveraging Linguistic Structure For Open Domain Information Extraction](https://md.research.elamur.ai/free/en/papers/angeli-2015-leveraging-linguistic-structure-open-domain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabor Angeli, Melvin Jose Johnson Premkumar, Christopher D. Manning*2015 · 923 citations*
10. **[Compositional Semantic Parsing on Semi-Structured Tables](https://md.research.elamur.ai/free/en/papers/pasupat-2015-compositional-semantic-parsing-semi-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Panupong Pasupat, Percy Liang*2015 · 918 citations*
11. **[Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths](https://md.research.elamur.ai/free/en/papers/xu-2015-classifying-relations-long-short-term/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yan Xu, Lili Mou, Ge Li, et al.*2015 · 775 citations*
12. **[Dice Loss for Data-imbalanced NLP Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-dice-loss-data-imbalanced-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al.*2020 · 735 citations*
13. **[Learning Word Vectors for 157 Languages](https://md.research.elamur.ai/free/en/papers/grave-2018-learning-word-vectors-157-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Edouard Grave, Piotr Bojanowski, Prakhar Gupta, et al.*2018 · 646 citations*
14. **[Event Extraction by Answering (Almost) Natural Questions](https://md.research.elamur.ai/free/en/papers/du-2020-event-extraction-answering-almost-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinya Du, Claire Cardie*2020 · 604 citations*
15. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
16. **[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*
17. **[LLM-Pruner: On the Structural Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-llm-pruner-structural-pruning-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xinyin Ma, Gongfan Fang, Xinchao Wang*2023 · 452 citations*
18. **[GPT-NER: Named Entity Recognition via Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*
19. **[Event Extraction as Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/liu-2020-event-extraction-as-machine-reading/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jian Liu, Yubo Chen, Kang Liu, et al.*2020 · 422 citations*
20. **[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*
21. **[Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents](https://md.research.elamur.ai/free/en/papers/xiao-2021-lawformer-pre-trained-language-model/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Chaojun Xiao, Xueyu Hu, Zhiyuan Liu, et al.*2021 · 396 citations*
22. **[A Unified Generative Framework for Various NER Subtasks](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-various-ner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Tao Gui, Junqi Dai, et al.*2021 · 394 citations*
23. **[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*
24. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
25. **[Few-NERD: A Few-shot Named Entity Recognition Dataset](https://md.research.elamur.ai/free/en/papers/ding-2021-few-nerd-few-shot-named/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Ding, Guangwei Xu, Yulin Chen, et al.*2021 · 336 citations*
26. [**Learning to Simplify Sentences with Quasi-Synchronous Grammar and Integer Programming**Kristian Woodsend, Mirella Lapata*2011 · 335 citations*](https://md.research.elamur.ai/free/en/papers/woodsend-2011-learning-simplify-sentences-quasi-synchronous/)
27. **[Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense](https://md.research.elamur.ai/free/en/papers/krishna-2023-paraphrasing-evades-detectors-ai-generated/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al.*2023 · 310 citations*
28. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*
29. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
30. [**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/)
31. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 272 citations*
32. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
33. **[CorefQA: Coreference Resolution as Query-based Span Prediction](https://md.research.elamur.ai/free/en/papers/wu-2020-corefqa-coreference-resolution-as-query/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Wu, Fei Wang, Arianna Yuan, et al.*2020 · 256 citations*
34. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
35. **[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 · 232 citations*
36. **[A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages](https://md.research.elamur.ai/free/en/papers/suarez-2020-monolingual-approach-contextualized-word-embeddings/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot*2020 · 222 citations*
37. **[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 · 206 citations*
38. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction arXiv:2304.08085**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/)
39. **[A Dataset of Syntactic-Ngrams over Time from a Very Large Corpus of English Books](https://md.research.elamur.ai/free/en/papers/goldberg-2013-dataset-syntactic-ngrams-over-time/) [Joint Conference on Lexical and Computational Semantics (*SEM), Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity](https://md.research.elamur.ai/free/en/venues/joint-conference-on-lexical-and-computational-semantics-sem-proceedings-of-the-2/)**Yoav Goldberg, Jon Orwant*2013 · 192 citations*
40. **[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*
41. **[Packed Levitated Marker for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/ye-2022-packed-levitated-marker-entity-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ye, Yankai Lin, Peng Li, et al.*2022 · 189 citations*
42. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models arXiv:2310.00746**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
43. **[Investigating Cultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-investigating-cultural-alignment-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Badr AlKhamissi, Muhammad ElNokrashy, Mai Alkhamissi, et al.*2024 · 183 citations*
44. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
45. **[Word-Level Coreference Resolution](https://md.research.elamur.ai/free/en/papers/dobrovolskii-2021-word-level-coreference-resolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vladimir Dobrovolskii*2021 · 146 citations*
46. **[How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*
47. **[Revealing the Myth of Higher-Order Inference in Coreference Resolution](https://md.research.elamur.ai/free/en/papers/xu-2020-revealing-myth-higher-order-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyan Xu, Jinho D. Choi*2020 · 145 citations*
48. [**Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness arXiv:2304.11633**Bo Li, Gexiang Fang, Yang Yang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-chatgpt-s-information-extraction/)
49. **[Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 133 citations*
50. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
51. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
52. [**UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition arXiv:2308.03279**Wenxuan Zhou, Sheng Zhang, Yu Gu, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-universalner-targeted-distillation-large-language/)
53. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
54. [**How would Stance Detection Techniques Evolve after the Launch of ChatGPT? arXiv:2212.14548**Bowen Zhang, Daijun Ding, Liwen Jing, et al.*2022 · 116 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-would-stance-detection-techniques-evolve/)
55. **[Coreference Resolution without Span Representations](https://md.research.elamur.ai/free/en/papers/kirstain-2021-coreference-resolution-without-span-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuval Kirstain, Ori Ram, Omer Levy*2021 · 109 citations*
56. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
57. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
58. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 96 citations*
59. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
60. **[FineSurE: Fine-grained Summarization Evaluation using LLMs](https://md.research.elamur.ai/free/en/papers/song-2024-finesure-fine-grained-summarization-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hwanjun Song, Hang Su, Igor Shalyminov, et al.*2024 · 92 citations*
61. **[GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities](https://md.research.elamur.ai/free/en/papers/ghosh-2024-gama-large-audio-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sreyan Ghosh, Sonal Kumar, Ashish Seth, et al.*2024 · 87 citations*
62. [**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/)
63. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
64. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations*
65. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
66. [**TableLlama: Towards Open Large Generalist Models for Tables arXiv:2311.09206**Tianshu Zhang, Xiang Yue, Yifei Li, et al.*2023 · 82 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-tablellama-towards-open-large-generalist/)
67. **[AutoRE: Document-Level Relation Extraction with Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2024-autore-document-level-relation-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lilong Xue, Dan Zhang, Yuxiao Dong, et al.*2024 · 79 citations*
68. **[Coreference Resolution through a seq2seq Transition-Based System](https://md.research.elamur.ai/free/en/papers/bohnet-2023-coreference-resolution-through-seq2seq-transition/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Bernd Bohnet, Chris Alberti, Michael Collins*2023 · 77 citations*
69. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
70. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
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