---
title: "Who cites Joshua Maynez — page 3 — 5,987 citing papers"
description: "5,987 papers of the Elamur Research library cite the works of Joshua Maynez, found in their bibliographies · page 3 of 15 · 201–300; the most…"
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# Who cites Joshua Maynez

6,699 citations of their works from 5,987 papers of our library (of the 149,439 whose bibliographies we read) · 1,482 with a page here, the most cited first · page 3 of 15 · 201–300 · [← Joshua Maynez](https://md.research.elamur.ai/free/en/authors/joshua-maynez/)

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201. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*
202. **[QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization](https://md.research.elamur.ai/free/en/papers/fabbri-2022-qafacteval-improved-qa-based-factual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 292 citations*
203. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
204. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
205. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
206. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines arXiv:2310.03714**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
207. [**Larger language models do in-context learning differently arXiv:2303.03846**Jerry Wei, Jason Wei, Yi Tay, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-larger-language-models-context-learning/)
208. [**MEGA: Multilingual Evaluation of Generative AI arXiv:2303.12528**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
209. **[AlignScore: Evaluating Factual Consistency with A Unified Alignment Function](https://md.research.elamur.ai/free/en/papers/zha-2023-alignscore-evaluating-factual-consistency-unified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuheng Zha, Yichi Yang, Ruichen Li, et al.*2023 · 284 citations*
210. [**A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models arXiv:2303.10420**Junjie Ye, Xuanting Chen, Nuo Xu, et al.*2023 · 283 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-comprehensive-capability-analysis-gpt-3/)
211. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators arXiv:2209.10063**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 281 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
212. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 280 citations*
213. **[An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 279 citations*
214. **[TRUE: Re-evaluating Factual Consistency Evaluation](https://md.research.elamur.ai/free/en/papers/honovich-2022-true-re-evaluating-factual-consistency/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Or Honovich, Roee Aharoni, Jonathan Herzig, et al.*2022 · 279 citations*
215. **[A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 277 citations*
216. **[Are We on the Right Way for Evaluating Large Vision-Language Models?](https://md.research.elamur.ai/free/en/papers/chen-2024-right-way-evaluating-large-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2024 · 277 citations*
217. **[LLM-QAT: Data-Free Quantization Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 276 citations*
218. [**Corrective Retrieval Augmented Generation arXiv:2401.15884**Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/yan-2024-corrective-retrieval-augmented-generation/)
219. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models arXiv:2410.05229**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
220. [**Reducing Activation Recomputation in Large Transformer Models arXiv:2205.05198**Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.*2022 · 273 citations*](https://md.research.elamur.ai/free/en/papers/korthikanti-2022-reducing-activation-recomputation-large-transformer/)
221. **[Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters](https://md.research.elamur.ai/free/en/papers/wang-2023-understanding-chain-thought-prompting-empirical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boshi Wang, Sewon Min, Xiang Deng, et al.*2023 · 272 citations*
222. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
223. **[Large Language Models Are Zero-Shot Time Series Forecasters](https://md.research.elamur.ai/free/en/papers/gruver-2023-large-language-models-zero-shot/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nate Gruver, Marc Finzi, Shikai Qiu, et al.*2023 · 268 citations*
224. **[OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments](https://md.research.elamur.ai/free/en/papers/xie-2024-osworld-benchmarking-multimodal-agents-open/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.*2024 · 264 citations*
225. **[The Effect of Sampling Temperature on Problem Solving in Large Language Models](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Renze*2024 · 263 citations*
226. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
227. **[Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions](https://md.research.elamur.ai/free/en/papers/pezeshkpour-2023-large-language-models-sensitivity-order/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pouya Pezeshkpour, Estevam Hruschka*2023 · 261 citations*
228. [**Scaling Relationship on Learning Mathematical Reasoning with Large Language Models arXiv:2308.01825**Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-scaling-relationship-learning-mathematical-reasoning/)
229. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations*
230. **[CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2021-cliff-contrastive-learning-improving-faithfulness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuyang Cao, Lu Wang*2021 · 260 citations*
231. [**Contrastive Decoding: Open-ended Text Generation as Optimization arXiv:2210.15097**Xiang Lisa Li, Ari Holtzman, Daniel Fried, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-contrastive-decoding-open-ended-text/)
232. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
233. **[InternVideo2: Scaling Foundation Models for Multimodal Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 253 citations*
234. **[GPT-RE: In-context Learning for Relation Extraction using Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 253 citations*
235. [**Personality Traits in Large Language Models arXiv:2307.00184**Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/serapio-garcia-2023-personality-traits-large-language-models/)
236. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment arXiv:2304.06767**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
237. **[Trusting Your Evidence: Hallucinate Less with Context-aware Decoding](https://md.research.elamur.ai/free/en/papers/shi-2024-trusting-your-evidence-hallucinate-less/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Weijia Shi, Xiaochuang Han, Mike Lewis, et al.*2024 · 249 citations*
238. **[Language Models can Solve Computer Tasks](https://md.research.elamur.ai/free/en/papers/kim-2023-language-models-solve-computer-tasks/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Geunwoo Kim, Pierre Baldi, Stephen McAleer*2023 · 249 citations*
239. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity arXiv:2301.12867**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 249 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
240. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture arXiv:2306.16092**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
241. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 246 citations*
242. **[Hallucinations in Large Multilingual Translation Models](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.*2023 · 244 citations*
243. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought arXiv:2210.01240**Abulhair Saparov, He He*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/)
244. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization arXiv:2212.12017**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
245. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset arXiv:2309.11998**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
246. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
247. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding arXiv:2306.02858**Hang Zhang, Xin Li, Lidong Bing*2023 · 238 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
248. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
249. **[Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision](https://md.research.elamur.ai/free/en/papers/sun-2023-principle-driven-self-alignment-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.*2023 · 236 citations*
250. [**What learning algorithm is in-context learning? Investigations with linear models arXiv:2211.15661**Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/)
251. **[Evaluating Open-Domain Question Answering in the Era of Large Language Models](https://md.research.elamur.ai/free/en/papers/kamalloo-2023-evaluating-open-domain-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.*2023 · 233 citations*
252. **[MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.*2024 · 232 citations*
253. [**GAIA: a benchmark for General AI Assistants arXiv:2311.12983**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
254. **[Detecting Hallucinated Content in Conditional Neural Sequence Generation](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunting Zhou, Graham Neubig, Jiatao Gu, et al.*2021 · 232 citations*
255. **[Beyond neural scaling laws: beating power law scaling via data pruning](https://md.research.elamur.ai/free/en/papers/sorscher-2022-neural-scaling-laws-beating-power/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.*2022 · 231 citations*
256. [**Self-critiquing models for assisting human evaluators arXiv:2206.05802**William Saunders, Catherine Yeh, Jeff Wu, et al.*2022 · 228 citations*](https://md.research.elamur.ai/free/en/papers/saunders-2022-self-critiquing-models-assisting-human/)
257. [**Tower: An Open Multilingual Large Language Model for Translation-Related Tasks arXiv:2402.17733**Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.*2024 · 227 citations*](https://md.research.elamur.ai/free/en/papers/alves-2024-tower-open-multilingual-large-language/)
258. [**How Language Model Hallucinations Can Snowball arXiv:2305.13534**Muru Zhang, Ofir Press, William Merrill, et al.*2023 · 226 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-language-model-hallucinations-snowball/)
259. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving arXiv:2309.17452**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 225 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
260. [**Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting arXiv:2305.07004**Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-all-languages-created-equal-llms/)
261. [**Specializing Smaller Language Models towards Multi-Step Reasoning arXiv:2301.12726**Yao Fu, Hao Peng, Litu Ou, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-specializing-smaller-language-models-towards/)
262. **[GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information](https://md.research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Qiao Jin, Yifan Yang, Qingyu Chen, et al.*2023 · 223 citations*
263. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models arXiv:2405.17428**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 222 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
264. [**Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP arXiv:2212.14024**Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.*2022 · 222 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/)
265. **[PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change](https://md.research.elamur.ai/free/en/papers/valmeekam-2022-planbench-extensible-benchmark-evaluating-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.*2022 · 222 citations*
266. **[A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages](https://md.research.elamur.ai/free/en/papers/suarez-2020-monolingual-approach-contextualized-word-embeddings/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot*2020 · 222 citations*
267. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 221 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
268. [**AlpaGasus: Training A Better Alpaca with Fewer Data arXiv:2307.08701**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/)
269. **[Distilling Reasoning Capabilities into Smaller Language Models](https://md.research.elamur.ai/free/en/papers/shridhar-2023-distilling-reasoning-capabilities-into-smaller/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan*2023 · 219 citations*
270. [**FOLIO: Natural Language Reasoning with First-Order Logic arXiv:2209.00840**Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/)
271. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models arXiv:2308.16149**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 218 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
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273. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors arXiv:2308.10848**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/)
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275. [**Safe RLHF: Safe Reinforcement Learning from Human Feedback arXiv:2310.12773**Josef Dai, Xuehai Pan, Ruiyang Sun, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-safe-rlhf-safe-reinforcement-learning/)
276. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
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279. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders arXiv:2404.05961**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 213 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/)
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285. [**ChemCrow: Augmenting large-language models with chemistry tools arXiv:2304.05376**Andres M Bran, Sam Cox, Oliver Schilter, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/bran-2023-chemcrow-augmenting-large-language/)
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287. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
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289. [**SALMONN: Towards Generic Hearing Abilities for Large Language Models arXiv:2310.13289**Changli Tang, Wenyi Yu, Guangzhi Sun, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/)
290. [**Internet-augmented language models through few-shot prompting for open-domain question answering arXiv:2203.05115**Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, et al.*2022 · 209 citations*](https://md.research.elamur.ai/free/en/papers/lazaridou-2022-internet-augmented-language-models-through/)
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293. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 arXiv:2311.10702**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
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299. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears arXiv:2304.05302**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
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