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title: "Language models & pretraining — papers, page 5"
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# 🧠 Language models & pretraining

1,079 papers · page 5 of 12 · 326–425 · 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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326. [**Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/)
327. [**SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization**Haoming Jiang, Pengcheng He, Weizhu Chen, et al.*2020 · 291 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/)
328. [**Neural language models as psycholinguistic subjects: Representations of syntactic state**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2019 · 291 citations*](https://md.research.elamur.ai/free/en/papers/futrell-2019-neural-language-models-as-psycholinguistic/)
329. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
330. [**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/)
331. [**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/)
332. [**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/)
333. [**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/)
334. [**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/)
335. [**HuatuoGPT, Towards Taming Language Model to Be a Doctor**Hongbo Zhang, Junying Chen, Feng Jiang, et al.*2023 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/)
336. [**Otter: A Multi-Modal Model with In-Context Instruction Tuning**Bo Li, Yuanhan Zhang, Liangyu Chen, et al.*2023 · 279 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-otter-multi-modal-model-context/)
337. [**Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 279 citations*](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/)
338. [**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/)
339. [**An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/)
340. [**What do RNN Language Models Learn about Filler-Gap Dependencies?**Ethan Wilcox, Roger Levy, Takashi Morita, et al.*2018 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2018-rnn-language-models-learn-about/)
341. [**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/)
342. [**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/)
343. [**Text Classification Using Label Names Only: A Language Model Self-Training Approach**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/)
344. [**JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models**Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/chao-2024-jailbreakbench-open-robustness-benchmark-jailbreaking/)
345. [**Kosmos-2: Grounding Multimodal Large Language Models to the World**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 272 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
346. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/)
347. [**XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/)
348. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
349. [**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/)
350. [**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/)
351. [**Injecting Numerical Reasoning Skills into Language Models**Mor Geva, Ankit Gupta, Jonathan Berant*2020 · 268 citations*](https://md.research.elamur.ai/free/en/papers/geva-2020-injecting-numerical-reasoning-skills-into/)
352. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
353. [**Prometheus: Inducing Fine-grained Evaluation Capability in Language Models**Seungone Kim, Jamin Shin, Yejin Cho, et al.*2023 · 267 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/)
354. [**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/)
355. [**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/)
356. [**LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models**Yukang Chen, Shengju Qian, Haotian Tang, et al.*2023 · 265 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-longlora-efficient-fine-tuning-long/)
357. [**Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages**Kelechi Ogueji, Yuxin Zhu, Jimmy Lin*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/ogueji-2021-small-data-no-problem-exploring/)
358. [**HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 264 citations*](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/)
359. [**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/)
360. [**Towards Understanding and Mitigating Social Biases in Language Models**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 263 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
361. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
362. [**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/)
363. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
364. [**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/)
365. [**Condenser: a Pre-training Architecture for Dense Retrieval**Luyu Gao, Jamie Callan*2021 · 261 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-condenser-pre-training-architecture-dense/)
366. [**Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks**Haoyang Huang, Yaobo Liang, Nan Duan, et al.*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/)
367. [**Large Language Models for Data Annotation and Synthesis: A Survey**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/)
368. [**On Extractive and Abstractive Neural Document Summarization with Transformer Language Models**Jonathan Pilault, Raymond Li, Sandeep Subramanian, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/pilault-2020-extractive-abstractive-neural-document-summarization/)
369. [**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/)
370. [**Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions**Pouya Pezeshkpour, Estevam Hruschka*2023 · 256 citations*](https://md.research.elamur.ai/free/en/papers/pezeshkpour-2023-large-language-models-sensitivity-order/)
371. [**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/)
372. [**QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 252 citations*](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/)
373. [**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/)
374. [**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/)
375. [**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/)
376. [**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/)
377. [**BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model**Alex Wang, Kyunghyun Cho*2019 · 249 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-bert-has-mouth-must-speak/)
378. [**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/)
379. [**OpenAI GPT-5 System Card**Aaditya Singh, Adam Fry, Adam Perelman, et al.*2025 · 247 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-openai-gpt-5-system-card/)
380. [**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/)
381. [**A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models**S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.*2024 · 246 citations*](https://md.research.elamur.ai/free/en/papers/tonmoy-2024-comprehensive-survey-hallucination-mitigation-techniques/)
382. [**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/)
383. [**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/)
384. [**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/)
385. [**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/)
386. [**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/)
387. [**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/)
388. [**LaMP: When Large Language Models Meet Personalization**Alireza Salemi, Sheshera Mysore, Michael Bendersky, et al.*2024 · 239 citations*](https://md.research.elamur.ai/free/en/papers/salemi-2024-lamp-when-large-language-models/)
389. [**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/)
390. [**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/)
391. [**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/)
392. [**Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/)
393. [**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/)
394. [**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/)
395. [**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/)
396. [**On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/)
397. [**Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models**Myra Cheng, Esin Durmus, Dan Jurafsky*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2023-marked-personas-natural-language-prompts/)
398. [**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/)
399. [**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/)
400. [**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/)
401. [**Qwen2-Audio Technical Report**Yunfei Chu, Jin Xu, Qian Yang, et al.*2024 · 232 citations*](https://md.research.elamur.ai/free/en/papers/chu-2024-qwen2-audio-technical-report/)
402. [**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/)
403. [**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/)
404. [**How Context Affects Language Models' Factual Predictions**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 231 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/)
405. [**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/)
406. [**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/)
407. [**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/)
408. [**Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction**Yubo Ma, Zehao Wang, Yixin Cao, et al.*2022 · 225 citations*](https://md.research.elamur.ai/free/en/papers/ma-2022-prompt-extraction-paie-prompting-argument/)
409. [**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/)
410. [**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/)
411. [**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/)
412. [**Improving Text Simplification Language Modeling Using Unsimplified Text Data**David Kauchak*2013 · 223 citations*](https://md.research.elamur.ai/free/en/papers/kauchak-2013-improving-text-simplification-language-modeling/)
413. [**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/)
414. [**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/)
415. [**How Language Model Hallucinations Can Snowball**Muru Zhang, Ofir Press, William Merrill, et al.*2023 · 221 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-language-model-hallucinations-snowball/)
416. [**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/)
417. [**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/)
418. [**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/)
419. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 219 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
420. [**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/)
421. [**Multilingual Translation from Denoising Pre-Training**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 219 citations*](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/)
422. [**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/)
423. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding**Hang Zhang, Xin Li, Lidong Bing*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
424. [**Distilling Reasoning Capabilities into Smaller Language Models**Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2023-distilling-reasoning-capabilities-into-smaller/)
425. [**Making Language Models Better Reasoners with Step-Aware Verifier**Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-making-language-models-better-reasoners/)

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