---
title: "Who cites Prafulla Dhariwal — page 4"
description: "12,963 papers of the Elamur Research library cite the works of Prafulla Dhariwal, found in their bibliographies · page 4 of 9 · 301–400; the most cited…"
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---
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# Who cites Prafulla Dhariwal

13,378 citations of their works from 12,963 papers of our library (of the 140,884 whose bibliographies we read) · 891 with a page here, the most cited first · page 4 of 9 · 301–400 · [← Prafulla Dhariwal](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/)

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301. [**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/)
302. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 285 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
303. [**API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/)
304. [**MEGA: Multilingual Evaluation of Generative AI**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
305. [**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/)
306. [**Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/)
307. [**OpenPrompt: An Open-source Framework for Prompt-learning**Ning Ding, Shengding Hu, Weilin Zhao, et al.*2022 · 278 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-openprompt-open-source-framework-prompt/)
308. [**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/)
309. [**LLM-QAT: Data-Free Quantization Aware Training for Large Language Models**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 275 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/)
310. [**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/)
311. [**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/)
312. [**Corrective Retrieval Augmented Generation**Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/yan-2024-corrective-retrieval-augmented-generation/)
313. [**Surface Form Competition: Why the Highest Probability Answer Isn't Always Right**Ari Holtzman, Peter West, Vered Shwartz, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/holtzman-2021-surface-form-competition-why-highest/)
314. [**Reducing Activation Recomputation in Large Transformer Models**Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.*2022 · 270 citations*](https://md.research.elamur.ai/free/en/papers/korthikanti-2022-reducing-activation-recomputation-large-transformer/)
315. [**Having Beer after Prayer? Measuring Cultural Bias in Large Language Models**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/)
316. [**An Explanation of In-context Learning as Implicit Bayesian Inference**Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.*2021 · 268 citations*](https://md.research.elamur.ai/free/en/papers/xie-2021-explanation-context-learning-implicit-bayesian/)
317. [**Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters**Boshi Wang, Sewon Min, Xiang Deng, et al.*2023 · 267 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-understanding-chain-thought-prompting-empirical/)
318. [**GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation**Kang Min Yoo, Dongju Park, Jaewook Kang, et al.*2021 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yoo-2021-gpt3mix-leveraging-large-scale-language/)
319. [**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/)
320. [**CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review**Dan Hendrycks, Collin Burns, Anya Chen, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-cuad-expert-annotated-nlp-dataset/)
321. [**Are We on the Right Way for Evaluating Large Vision-Language Models?**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2024 · 263 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-right-way-evaluating-large-vision/)
322. [**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/)
323. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
324. [**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/)
325. [**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/)
326. [**A Holistic Approach to Undesired Content Detection in the Real World**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/)
327. [**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/)
328. [**Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow**Xingchao Liu, Chengyue Gong, Qiang Liu*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/)
329. [**An Empirical Survey of Data Augmentation for Limited Data Learning in NLP**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)
330. [**GPT-RE: In-context Learning for Relation Extraction using Large Language Models**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/)
331. [**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/)
332. [**Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers**Damai Dai, Yutao Sun, Li Dong, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/)
333. [**Societal Biases in Language Generation: Progress and Challenges**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 252 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/)
334. [**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/)
335. [**Survey of Low-Resource Machine Translation**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/)
336. [**The Curse of Recursion: Training on Generated Data Makes Models Forget**Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, et al.*2023 · 250 citations*](https://md.research.elamur.ai/free/en/papers/shumailov-2023-curse-recursion-training-generated-data/)
337. [**Generating Datasets with Pretrained Language Models**Timo Schick, Hinrich Schutze*2021 · 250 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-generating-datasets-pretrained-language-models/)
338. [**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/)
339. [**LeanDojo: Theorem Proving with Retrieval-Augmented Language Models**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/)
340. [**RedPajama: an Open Dataset for Training Large Language Models**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 247 citations*](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/)
341. [**SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension**Bohao Li, Rui Wang, Guangzhi Wang, et al.*2023 · 247 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-seed-bench-benchmarking-multimodal-llms/)
342. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
343. [**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/)
344. [**Contrastive Decoding: Open-ended Text Generation as Optimization**Xiang Lisa Li, Ari Holtzman, Daniel Fried, et al.*2022 · 246 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-contrastive-decoding-open-ended-text/)
345. [**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/)
346. [**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/)
347. [**MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/)
348. [**Hallucinations in Large Multilingual Translation Models**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/)
349. [**Ignore Previous Prompt: Attack Techniques For Language Models**Fabio Perez, Ian Ribeiro*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-ignore-previous-prompt-attack-techniques/)
350. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache**Zirui Liu, Jiayi Yuan, Hongye Jin, et al.*2024 · 243 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/)
351. [**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/)
352. [**MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers**Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, et al.*2021 · 243 citations*](https://md.research.elamur.ai/free/en/papers/pillutla-2021-mauve-measuring-gap-between-neural/)
353. [**Automatic Detection of Machine Generated Text: A Critical Survey**Ganesh Jawahar, Muhammad Abdul-Mageed, Laks Lakshmanan V.S.*2020 · 243 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2020-automatic-detection-machine-generated-text/)
354. [**Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations**Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-synthetic-data-generation-large-language/)
355. [**ZeroGen: Efficient Zero-shot Learning via Dataset Generation**Jiacheng Ye, Jiahui Gao, Qintong Li, et al.*2022 · 242 citations*](https://md.research.elamur.ai/free/en/papers/ye-2022-zerogen-efficient-zero-shot-learning/)
356. [**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/)
357. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
358. [**In-context Examples Selection for Machine Translation**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/)
359. [**Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art**Patrick Lewis, Myle Ott, Jingfei Du, et al.*2020 · 240 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-pretrained-language-models-biomedical-clinical/)
360. [**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/)
361. [**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/)
362. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought**Abulhair Saparov, He He*2022 · 238 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/)
363. [**Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger**Fanchao Qi, Mukai Li, Yangyi Chen, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/qi-2021-hidden-killer-invisible-textual-backdoor/)
364. [**Multimodal Few-Shot Learning with Frozen Language Models**Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/tsimpoukelli-2021-multimodal-few-shot-learning-frozen/)
365. [**Noisy Channel Language Model Prompting for Few-Shot Text Classification**Sewon Min, Mike Lewis, Hannaneh Hajishirzi, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-noisy-channel-language-model-prompting/)
366. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 237 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
367. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
368. [**Reframing Instructional Prompts to GPTk's Language**Swaroop Mishra, Daniel Khashabi, Chitta Baral, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2022-reframing-instructional-prompts-gptk-s/)
369. [**Transformers learn in-context by gradient descent**Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/oswald-2022-transformers-learn-context-gradient-descent/)
370. [**COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs**Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, et al.*2020 · 235 citations*](https://md.research.elamur.ai/free/en/papers/hwang-2020-comet-atomic-2020-symbolic-neural/)
371. [**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/)
372. [**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/)
373. [**FUDGE: Controlled Text Generation With Future Discriminators**Kevin Yang, Dan Klein*2021 · 234 citations*](https://md.research.elamur.ai/free/en/papers/yang-2021-fudge-controlled-text-generation-future/)
374. [**The Importance of Modeling Social Factors of Language: Theory and Practice**Dirk Hovy, Diyi Yang*2021 · 234 citations*](https://md.research.elamur.ai/free/en/papers/hovy-2021-importance-modeling-social-factors-language/)
375. [**Evaluating Open-Domain Question Answering in the Era of Large Language Models**Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.*2023 · 233 citations*](https://md.research.elamur.ai/free/en/papers/kamalloo-2023-evaluating-open-domain-question-answering/)
376. [**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/)
377. [**MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?**Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.*2024 · 231 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/)
378. [**ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning**Petter Tornberg*2023 · 230 citations*](https://md.research.elamur.ai/free/en/papers/tornberg-2023-chatgpt-4-outperforms-experts-crowd/)
379. [**FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance**Lingjiao Chen, Matei Zaharia, James Zou*2023 · 229 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-frugalgpt-use-large-language-models/)
380. [**Detecting Hallucinated Content in Conditional Neural Sequence Generation**Chunting Zhou, Graham Neubig, Jiatao Gu, et al.*2021 · 229 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/)
381. [**Hurdles to Progress in Long-form Question Answering**Kalpesh Krishna, Aurko Roy, Mohit Iyyer*2021 · 227 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2021-hurdles-progress-long-form-question/)
382. [**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/)
383. [**What learning algorithm is in-context learning? Investigations with linear models**Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.*2022 · 224 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/)
384. [**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/)
385. [**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/)
386. [**A Survey of Hallucination in Large Foundation Models**Vipula Rawte, Amit Sheth, Amitava Das*2023 · 221 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-survey-hallucination-large-foundation-models/)
387. [**MedAlpaca — An Open-Source Collection of Medical Conversational AI Models and Training Data**Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, et al.*2023 · 221 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-medalpaca-open-source-collection-medical/)
388. [**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/)
389. [**Steering Language Models With Activation Engineering**Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/turner-2023-steering-language-models-activation-engineering/)
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