---
title: "Who cites Dario Amodei — page 2"
description: "3,856 papers of the Elamur Research library cite the works of Dario Amodei, found in their bibliographies · page 2 of 4 · 101–200; the most cited first."
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---
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# Who cites Dario Amodei

4,503 citations of their works from 3,856 papers of our library (of the 140,884 whose bibliographies we read) · 347 with a page here, the most cited first · page 2 of 4 · 101–200 · [← Dario Amodei](https://md.research.elamur.ai/free/en/authors/dario-amodei/)

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101. [**ChatDev: Communicative Agents for Software Development**Chen Qian, Wei Liu, Hongzhang Liu, et al.*2023 · 373 citations*](https://md.research.elamur.ai/free/en/papers/qian-2023-chatdev-communicative-agents-software/)
102. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
103. [**Towards Understanding Sycophancy in Language Models**Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.*2023 · 354 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2023-towards-understanding-sycophancy-language-models/)
104. [**BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/)
105. [**TinyLlama: An Open-Source Small Language Model**Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.*2024 · 350 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-tinyllama-open-source-small-language/)
106. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
107. [**Improving alignment of dialogue agents via targeted human judgements**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 346 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
108. [**Toxicity in chatgpt: Analyzing persona-assigned language models**Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/deshpande-2023-toxicity-chatgpt-analyzing-persona-assigned/)
109. [**Complexity-Based Prompting for Multi-Step Reasoning**Yao Fu, Hao Peng, Ashish Sabharwal, et al.*2022 · 343 citations*](https://md.research.elamur.ai/free/en/papers/fu-2022-complexity-based-prompting-multi-step/)
110. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 339 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
111. [**Large Language Models for Information Retrieval: A Survey**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/)
112. [**Solving math word problems with process- and outcome-based feedback**Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.*2022 · 334 citations*](https://md.research.elamur.ai/free/en/papers/uesato-2022-solving-math-word-problems-process/)
113. [**UL2: Unifying Language Learning Paradigms**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 334 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
114. [**AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models**Xiaogeng Liu, Nan Xu, Muhao Chen, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-autodan-generating-stealthy-jailbreak-prompts/)
115. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
116. [**Search-based Neural Structured Learning for Sequential Question Answering**Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang*2017 · 327 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2017-search-based-neural-structured-learning/)
117. [**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/)
118. [**Are Emergent Abilities of Large Language Models a Mirage?**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 323 citations*](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/)
119. [**Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding**Sicong Leng, Hang Zhang, Guanzheng Chen, et al.*2023 · 317 citations*](https://md.research.elamur.ai/free/en/papers/leng-2023-mitigating-object-hallucinations-large-vision/)
120. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
121. [**Faith and Fate: Limits of Transformers on Compositionality**Nouha Dziri, Ximing Lu, Melanie Sclar, et al.*2023 · 313 citations*](https://md.research.elamur.ai/free/en/papers/dziri-2023-faith-fate-limits-transformers-compositionality/)
122. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 312 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/)
123. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 307 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
124. [**Discovering Language Model Behaviors with Model-Written Evaluations**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 305 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
125. [**How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources**Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.*2023 · 304 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-far-camels-go-exploring-state/)
126. [**Carbon Emissions and Large Neural Network Training**David Patterson, Joseph Gonzalez, Quoc Le, et al.*2021 · 304 citations*](https://md.research.elamur.ai/free/en/papers/patterson-2021-carbon-emissions-large-neural-network/)
127. [**ZeRO-Offload: Democratizing Billion-Scale Model Training**Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.*2021 · 302 citations*](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)
128. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
129. [**Character-LLM: A Trainable Agent for Role-Playing**Yunfan Shao, Linyang Li, Junqi Dai, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/)
130. [**InternLM2 Technical Report**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
131. [**Prompting Large Language Model for Machine Translation: A Case Study**Biao Zhang, Barry Haddow, Alexandra Birch*2023 · 293 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/)
132. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
133. [**Can language models learn from explanations in context?**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 288 citations*](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/)
134. [**SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 287 citations*](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/)
135. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 280 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
136. [**Large Language Models for Mathematical Reasoning: Progresses and Challenges**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 279 citations*](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/)
137. [**Larger language models do in-context learning differently**Jerry Wei, Jason Wei, Yi Tay, et al.*2023 · 277 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-larger-language-models-context-learning/)
138. [**Llemma: An Open Language Model For Mathematics**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 275 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
139. [**Scaling Laws for Reward Model Overoptimization**Leo Gao, John Schulman, Jacob Hilton*2022 · 266 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-scaling-laws-reward-model-overoptimization/)
140. [**Towards Measuring the Representation of Subjective Global Opinions in Language Models**Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.*2023 · 262 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2023-towards-measuring-representation-subjective-global/)
141. [**The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 259 citations*](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/)
142. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
143. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
144. [**DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale**Samyam Rajbhandari, Conglong Li, Zhewei Yao, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/rajbhandari-2022-deepspeed-moe-advancing-mixture-experts/)
145. [**TAPEX: Table Pre-training via Learning a Neural SQL Executor**Qian Liu, Bei Chen, Jiaqi Guo, et al.*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-tapex-table-pre-training-learning/)
146. [**Scaling Relationship on Learning Mathematical Reasoning with Large Language Models**Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-scaling-relationship-learning-mathematical-reasoning/)
147. [**Personality Traits in Large Language Models**Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.*2023 · 251 citations*](https://md.research.elamur.ai/free/en/papers/serapio-garcia-2023-personality-traits-large-language-models/)
148. [**Measuring Faithfulness in Chain-of-Thought Reasoning**Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.*2023 · 249 citations*](https://md.research.elamur.ai/free/en/papers/lanham-2023-measuring-faithfulness-chain-thought-reasoning/)
149. [**DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/)
150. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
151. [**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/)
152. [**Tree of Attacks: Jailbreaking Black-Box LLMs Automatically**Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.*2023 · 245 citations*](https://md.research.elamur.ai/free/en/papers/mehrotra-2023-tree-attacks-jailbreaking-black-box/)
153. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 243 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
154. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 241 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
155. [**Language Models can Solve Computer Tasks**Geunwoo Kim, Pierre Baldi, Stephen McAleer*2023 · 239 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-language-models-solve-computer-tasks/)
156. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 239 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
157. [**Perceiver: General Perception with Iterative Attention**Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/jaegle-2021-perceiver-general-perception-iterative-attention/)
158. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
159. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 235 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
160. [**Generative Language Modeling for Automated Theorem Proving**Stanislas Polu, Ilya Sutskever*2020 · 235 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
161. [**BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage**Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.*2022 · 234 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2022-blenderbot-3-deployed-conversational-agent/)
162. [**Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision**Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-principle-driven-self-alignment-language/)
163. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 227 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
164. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
165. [**Baseline Defenses for Adversarial Attacks Against Aligned Language Models**Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-baseline-defenses-adversarial-attacks-against/)
166. [**Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting**Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-all-languages-created-equal-llms/)
167. [**Specializing Smaller Language Models towards Multi-Step Reasoning**Yao Fu, Hao Peng, Litu Ou, et al.*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-specializing-smaller-language-models-towards/)
168. [**Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models**Seungone Kim, Juyoung Suk, Shayne Longpre, et al.*2024 · 220 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/)
169. [**Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection**Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/greshake-2023-ve-signed-up-compromising-real/)
170. [**Beyond neural scaling laws: beating power law scaling via data pruning**Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.*2022 · 220 citations*](https://md.research.elamur.ai/free/en/papers/sorscher-2022-neural-scaling-laws-beating-power/)
171. [**Transformer Memory as a Differentiable Search Index**Yi Tay, Vinh Q. Tran, Mostafa Dehghani, et al.*2022 · 220 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transformer-memory-differentiable-search-index/)
172. [**Med-HALT: Medical Domain Hallucination Test for Large Language Models**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*2023 · 219 citations*](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/)
173. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 219 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
174. [**Self-critiquing models for assisting human evaluators**William Saunders, Catherine Yeh, Jeff Wu, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/saunders-2022-self-critiquing-models-assisting-human/)
175. [**Unsupervised Question Decomposition for Question Answering**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/)
176. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
177. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/)
178. [**Teaching language models to support answers with verified quotes**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/)
179. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
180. [**Reinforced Self-Training (ReST) for Language Modeling**Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/)
181. [**Progress measures for grokking via mechanistic interpretability**Neel Nanda, Lawrence Chan, Tom Lieberum, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/nanda-2023-progress-measures-grokking-mechanistic-interpretability/)
182. [**Safe RLHF: Safe Reinforcement Learning from Human Feedback**Josef Dai, Xuehai Pan, Ruiyang Sun, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-safe-rlhf-safe-reinforcement-learning/)
183. [**LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models**Yen-Ting Lin, Yun-Nung Chen*2023 · 206 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-llm-eval-unified-multi-dimensional/)
184. [**Prompting GPT-3 To Be Reliable**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 206 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
185. [**LIMO: Less is More for Reasoning**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 204 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/)
186. [**TinyStories: How Small Can Language Models Be and Still Speak Coherent English?**Ronen Eldan, Yuanzhi Li*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/eldan-2023-tinystories-small-language-models-still/)
187. [**Recursively Summarizing Books with Human Feedback**Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.*2021 · 201 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-recursively-summarizing-books-human-feedback/)
188. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
189. [**Concrete Problems in AI Safety**Dario Amodei, Chris Olah, Jacob Steinhardt, et al.*2016 · 198 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2016-concrete-problems-ai-safety/)
190. [**Scalable Extraction of Training Data from (Production) Language Models**Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.*2023 · 197 citations*](https://md.research.elamur.ai/free/en/papers/nasr-2023-scalable-extraction-training-data-production/)
191. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
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