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title: "Language models & pretraining — papers, page 3"
description: "Language models & pretraining: 1,079 papers of the Elamur Research library · page 3 of 12 · 126–225, the most cited first."
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# 🧠 Language models & pretraining

1,079 papers · page 3 of 12 · 126–225 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

Models that learn a language from raw text, and how they are pretrained, tuned and prompted.

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126. [**WizardLM: Empowering large pre-trained language models to follow complex instructions**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 729 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/)
127. [**Learning To Retrieve Prompts for In-Context Learning**Ohad Rubin, Jonathan Herzig, Jonathan Berant*2021 · 717 citations*](https://md.research.elamur.ai/free/en/papers/rubin-2021-learning-retrieve-prompts-context-learning/)
128. [**SGLang: Efficient Execution of Structured Language Model Programs**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 710 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/)
129. [**Scalable Modified Kneser-Ney Language Model Estimation**Kenneth Heafield, Ivan Pouzyrevsky, Jonathan H. Clark, et al.*2013 · 709 citations*](https://md.research.elamur.ai/free/en/papers/heafield-2013-scalable-modified-kneser-ney-language/)
130. [**TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/)
131. [**Explain Yourself! Leveraging Language Models for Commonsense Reasoning**Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, et al.*2019 · 690 citations*](https://md.research.elamur.ai/free/en/papers/rajani-2019-explain-yourself-leveraging-language-models/)
132. [**Automatic Chain of Thought Prompting in Large Language Models**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2022 · 688 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-automatic-chain-thought-prompting-large/)
133. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 687 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
134. [**Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 684 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)
135. [**DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation**Yizhe Zhang, Siqi Sun, Michel Galley, et al.*2019 · 684 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/)
136. [**Large Language Models Are Human-Level Prompt Engineers**Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.*2022 · 677 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/)
137. [**Mask-Predict: Parallel Decoding of Conditional Masked Language Models**Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al.*2019 · 671 citations*](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/)
138. [**Well-Read Students Learn Better: On the Importance of Pre-training Compact Models**Iulia Turc, Ming-Wei Chang, Kenton Lee, et al.*2019 · 671 citations*](https://md.research.elamur.ai/free/en/papers/turc-2019-well-read-students-learn-better/)
139. [**Red Teaming Language Models with Language Models**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 665 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/)
140. [**An Improved Error Model for Noisy Channel Spelling Correction**Eric Brill, Robert C. Moore*2000 · 661 citations*](https://md.research.elamur.ai/free/en/papers/brill-2000-improved-error-model-noisy-channel/)
141. [**Jailbroken: How Does LLM Safety Training Fail?**Alexander Wei, Nika Haghtalab, Jacob Steinhardt*2023 · 659 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbroken-llm-safety-training-fail/)
142. [**Instruction Tuning with GPT-4**Baolin Peng, Chunyuan Li, Pengcheng He, et al.*2023 · 651 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-instruction-tuning-gpt-4/)
143. [**HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models**Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.*2023 · 646 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)
144. [**CoCa: Contrastive Captioners are Image-Text Foundation Models**Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/)
145. [**Persistent Anti-Muslim Bias in Large Language Models**Abubakar Abid, Maheen Farooqi, James Zou*2021 · 640 citations*](https://md.research.elamur.ai/free/en/papers/abid-2021-persistent-anti-muslim-bias-large/)
146. [**DAPO: An Open-Source LLM Reinforcement Learning System at Scale**Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.*2025 · 634 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-dapo-open-source-llm-reinforcement/)
147. [**Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models**Muhammad Maaz, Hanoona Rasheed, Salman Khan, et al.*2023 · 634 citations*](https://md.research.elamur.ai/free/en/papers/maaz-2023-video-chatgpt-towards-detailed-video/)
148. [**Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation**Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.*2023 · 632 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-your-code-generated-chatgpt-really/)
149. [**Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine**Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, et al.*2023 · 626 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2023-chatgpt-good-translator-yes-gpt/)
150. [**LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 623 citations*](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/)
151. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues?**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 617 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
152. [**Advances in Pre-Training Distributed Word Representations**Tomas Mikolov, Edouard Grave, Piotr Bojanowski, et al.*2017 · 614 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2017-advances-pre-training-distributed-word/)
153. [**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/)
154. [**Regularizing and Optimizing LSTM Language Models**Stephen Merity, Nitish Shirish Keskar, Richard Socher*2017 · 605 citations*](https://md.research.elamur.ai/free/en/papers/merity-2017-regularizing-optimizing-lstm-language-models/)
155. [**Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model**Shaden Smith, Mostofa Patwary, Brandon Norick, et al.*2022 · 595 citations*](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/)
156. [**Text Embeddings by Weakly-Supervised Contrastive Pre-training**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/)
157. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 590 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
158. [**Instruction-Following Evaluation for Large Language Models**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 586 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
159. [**A Robustly Optimized BERT Pre-training Approach with Post-training**Liu Zhuang, Lin Wayne, Shi Ya, et al.*2021 · 585 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2021-robustly-optimized-bert-pre-training/)
160. [**PhoBERT: Pre-trained language models for Vietnamese**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)
161. [**A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes**Yee Whye Teh*2006 · 571 citations*](https://md.research.elamur.ai/free/en/papers/teh-2006-hierarchical-bayesian-language-model-based/)
162. [**AudioLM: a Language Modeling Approach to Audio Generation**Zalan Borsos, Raphael Marinier, Damien Vincent, et al.*2022 · 570 citations*](https://md.research.elamur.ai/free/en/papers/borsos-2022-audiolm-language-modeling-approach-audio/)
163. [**Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting**Miles Turpin, Julian Michael, Ethan Perez, et al.*2023 · 568 citations*](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/)
164. [**Improving Factuality and Reasoning in Language Models through Multiagent Debate**Yilun Du, Shuang Li, Antonio Torralba, et al.*2023 · 564 citations*](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/)
165. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 564 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
166. [**AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models**Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.*2024 · 563 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/)
167. [**Plug and Play Language Models: A Simple Approach to Controlled Text Generation**Sumanth Dathathri, Andrea Madotto, Janice Lan, et al.*2019 · 562 citations*](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/)
168. [**Large Language Models Can Self-Improve**Jiaxin Huang, Shixiang Gu, Le Hou, et al.*2023 · 560 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/)
169. [**Galactica: A Large Language Model for Science**Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.*2022 · 558 citations*](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/)
170. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 556 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
171. [**gpt-oss-120b & gpt-oss-20b Model Card**OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.*2025 · 555 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-gpt-oss-120b-gpt-oss/)
172. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
173. [**Release Strategies and the Social Impacts of Language Models**Irene Solaiman, Miles Brundage, Jack Clark, et al.*2019 · 538 citations*](https://md.research.elamur.ai/free/en/papers/solaiman-2019-release-strategies-social-impacts-language/)
174. [**Jailbreaking Black Box Large Language Models in Twenty Queries**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 533 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
175. [**Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning**Armen Aghajanyan, Sonal Gupta, Luke Zettlemoyer*2021 · 530 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-intrinsic-dimensionality-explains-effectiveness-language/)
176. [**How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/)
177. [**MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 529 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/)
178. [**Gorilla: Large Language Model Connected with Massive APIs**Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.*2023 · 527 citations*](https://md.research.elamur.ai/free/en/papers/patil-2023-gorilla-large-language-model-connected/)
179. [**Large Language Models Can Be Easily Distracted by Irrelevant Context**Freda Shi, Xinyun Chen, Kanishka Misra, et al.*2023 · 525 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-large-language-models-easily-distracted/)
180. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 524 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
181. [**Instruction Tuning for Large Language Models: A Survey**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 515 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/)
182. [**Baichuan 2: Open Large-scale Language Models**Aiyuan Yang, Bin Xiao, Bingning Wang, et al.*2023 · 512 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-baichuan-2-open-large-scale/)
183. [**OpenAssistant Conversations — Democratizing Large Language Model Alignment**Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, et al.*2023 · 505 citations*](https://md.research.elamur.ai/free/en/papers/kopf-2023-openassistant-conversations-democratizing-large-language/)
184. [**Sentiment Analysis in the Era of Large Language Models: A Reality Check**Wenxuan Zhang, Yue Deng, Bing Liu, et al.*2023 · 505 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-sentiment-analysis-era-large-language/)
185. [**Few-shot Learning with Multilingual Language Models**Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/lin-2021-few-shot-learning-multilingual-language/)
186. [**Language Models are Multilingual Chain-of-Thought Reasoners**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 490 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
187. [**Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations**Peiyi Wang, Lei Li, Zhihong Shao, et al.*2024 · 482 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-math-shepherd-verify-reinforce-llms/)
188. [**REPLUG: Retrieval-Augmented Black-Box Language Models**Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.*2023 · 482 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/)
189. [**Enabling Large Language Models to Generate Text with Citations**Tianyu Gao, Howard Yen, Jiatong Yu, et al.*2023 · 477 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-enabling-large-language-models-generate/)
190. [**GLaM: Efficient Scaling of Language Models with Mixture-of-Experts**Nan Du, Yanping Huang, Andrew M. Dai, et al.*2021 · 474 citations*](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/)
191. [**Inference-Time Intervention: Eliciting Truthful Answers from a Language Model**Kenneth Li, Oam Patel, Fernanda Viegas, et al.*2023 · 473 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-inference-time-intervention-eliciting-truthful/)
192. [**Large Language Models: A Survey**Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.*2024 · 467 citations*](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/)
193. [**Evaluating Large Language Models in Theory of Mind Tasks**Michal Kosinski*2023 · 465 citations*](https://md.research.elamur.ai/free/en/papers/kosinski-2023-evaluating-large-language-models-theory/)
194. [**Masked Autoencoders Are Scalable Vision Learners**Kaiming He, Xinlei Chen, Saining Xie, et al.*2021 · 463 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-masked-autoencoders-scalable-vision-learners/)
195. [**Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 461 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/)
196. [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 459 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/)
197. [**Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned**Deep Ganguli, Liane Lovitt, Jackson Kernion, et al.*2022 · 456 citations*](https://md.research.elamur.ai/free/en/papers/ganguli-2022-red-teaming-language-models-reduce/)
198. [**LinkBERT: Pretraining Language Models with Document Links**Michihiro Yasunaga, Jure Leskovec, Percy Liang*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2022-linkbert-pretraining-language-models-document/)
199. [**Forest Rescoring: Faster Decoding with Integrated Language Models**Liang Huang, David Chiang*2007 · 452 citations*](https://md.research.elamur.ai/free/en/papers/huang-2007-forest-rescoring-faster-decoding-integrated/)
200. [**Show your work: Scratchpads for intermediate computation with language models***2021 · 448 citations*](https://md.research.elamur.ai/free/en/papers/al-2021-show-your-work-scratchpads-intermediate/)
201. [**LLM-Pruner: On the Structural Pruning of Large Language Models**Xinyin Ma, Gongfan Fang, Xinchao Wang*2023 · 447 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-llm-pruner-structural-pruning-large/)
202. [**Reading Level Assessment Using Support Vector Machines and Statistical Language Models**Sarah Schwarm, Mari Ostendorf*2005 · 447 citations*](https://md.research.elamur.ai/free/en/papers/schwarm-2005-reading-level-assessment-support-vector/)
203. [**HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization**Xingxing Zhang, Furu Wei, Ming Zhou*2019 · 446 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-hibert-document-level-pre-training/)
204. [**FinGPT: Open-Source Financial Large Language Models**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
205. [**How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models**Phillip Rust, Jonas Pfeiffer, Ivan Vulić, et al.*2021 · 444 citations*](https://md.research.elamur.ai/free/en/papers/rust-2021-how-good-is-your-tokenizer/)
206. [**Masked Language Model Scoring**Julian Salazar, Davis Liang, Toan Q. Nguyen, et al.*2020 · 444 citations*](https://md.research.elamur.ai/free/en/papers/salazar-2020-masked-language-model-scoring/)
207. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
208. [**Temporal Analysis of Language through Neural Language Models**Yoon Kim, Yi-I Chiu, Kentaro Hanaki, et al.*2014 · 439 citations*](https://md.research.elamur.ai/free/en/papers/kim-2014-temporal-analysis-language-through-neural/)
209. [**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/)
210. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
211. [**Self-Alignment Pretraining for Biomedical Entity Representations**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al.*2021 · 432 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/)
212. [**oLMpics — On what Language Model Pre-training Captures**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 432 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/)
213. [**Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly**Nora Kassner, Hinrich Schütze*2020 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2020-negated-misprimed-probes-pretrained-language/)
214. [**Analyzing the Structure of Attention in a Transformer Language Model**Jesse Vig, Yonatan Belinkov*2019 · 430 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/)
215. [**C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models**Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-c-eval-multi-level-multi/)
216. [**The Internal State of an LLM Knows When It's Lying**Amos Azaria, Tom Mitchell*2023 · 425 citations*](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/)
217. [**Probabilistic Top-Down Parsing and Language Modeling**Brian Roark*2001 · 424 citations*](https://md.research.elamur.ai/free/en/papers/roark-2001-probabilistic-top-down-parsing-language/)
218. [**Security and Privacy Challenges of Large Language Models: A Survey**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 422 citations*](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/)
219. [**Ethical and social risks of harm from Language Models**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 421 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
220. [**Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 419 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/)
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