---
title: "Who cites Diogo Almeida — page 4"
description: "13,639 papers of the Elamur Research library cite the works of Diogo Almeida, found in their bibliographies · page 4 of 8 · 301–400; the most cited first."
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---
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# Who cites Diogo Almeida

16,073 citations of their works from 13,639 papers of our library (of the 140,884 whose bibliographies we read) · 799 with a page here, the most cited first · page 4 of 8 · 301–400 · [← Diogo Almeida](https://md.research.elamur.ai/free/en/authors/diogo-almeida/)

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301. [**FOLIO: Natural Language Reasoning with First-Order Logic**Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.*2022 · 217 citations*](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/)
302. [**AlpaGasus: Training A Better Alpaca with Fewer Data**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 214 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/)
303. [**WildChat: 1M ChatGPT Interaction Logs in the Wild**Wenting Zhao, Xiang Ren, Jack Hessel, et al.*2024 · 213 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-wildchat-1m-chatgpt-interaction-logs/)
304. [**Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 212 citations*](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/)
305. [**Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4**Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-logical-reasoning-ability-chatgpt/)
306. [**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/)
307. [**GAIA: a benchmark for General AI Assistants**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
308. [**Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP**Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/)
309. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/)
310. [**Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/)
311. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 209 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/)
312. [**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/)
313. [**Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning**Pan Lu, Liang Qiu, Kai-Wei Chang, et al.*2022 · 209 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-dynamic-prompt-learning-policy-gradient/)
314. [**PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change**Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.*2022 · 209 citations*](https://md.research.elamur.ai/free/en/papers/valmeekam-2022-planbench-extensible-benchmark-evaluating-large/)
315. [**Sources of Hallucination by Large Language Models on Inference Tasks**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 208 citations*](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/)
316. [**Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation**Haoran Xu, Amr Sharaf, Yunmo Chen, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-contrastive-preference-optimization-pushing-boundaries/)
317. [**Exploring Human-Like Translation Strategy with Large Language Models**Zhiwei He, Tian Liang, Wenxiang Jiao, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-exploring-human-like-translation-strategy/)
318. [**Ring Attention with Blockwise Transformers for Near-Infinite Context**Hao Liu, Matei Zaharia, Pieter Abbeel*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ring-attention-blockwise-transformers-near/)
319. [**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/)
320. [**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/)
321. [**RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 204 citations*](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/)
322. [**LLM+P: Empowering Large Language Models with Optimal Planning Proficiency**Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.*2023 · 204 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-llm-p-empowering-large-language/)
323. [**How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs**Yi Zeng, Hongpeng Lin, Jingwen Zhang, et al.*2024 · 202 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-how-johnny-can-persuade-llms/)
324. [**SALMONN: Towards Generic Hearing Abilities for Large Language Models**Changli Tang, Wenyi Yu, Guangzhi Sun, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/)
325. [**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/)
326. [**DeepSeek-VL: Towards Real-World Vision-Language Understanding**Haoyu Lu, Wen Liu, Bo Zhang, et al.*2024 · 201 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-deepseek-vl-real-world/)
327. [**SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization**Hyunwoo Kim, Jack Hessel, Liwei Jiang, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-soda-million-scale-dialogue-distillation/)
328. [**IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages**Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.*2023 · 200 citations*](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/)
329. [**Aligning Large Language Models with Human: A Survey**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
330. [**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/)
331. [**Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 198 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/)
332. [**A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/)
333. [**Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias**Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-large-language-model-attributed-training/)
334. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/)
335. [**ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search**Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.*2024 · 197 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-rest-mcts-llm-self-training/)
336. [**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/)
337. [**Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 196 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
338. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 195 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
339. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
340. [**What matters when building vision-language models?**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/)
341. [**Towards Faithful Model Explanation in NLP: A Survey**Qing Lyu, Marianna Apidianaki, Chris Callison-Burch*2024 · 194 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2024-faithful-model-explanation-nlp-survey/)
342. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
343. [**Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback**Viet Lai, Chien Nguyen, Nghia Ngo, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-okapi-instruction-tuned-large-language/)
344. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
345. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/)
346. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
347. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
348. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
349. [**GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4**Tom Kocmi, Christian Federmann*2023 · 191 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2023-gemba-mqm-detecting-translation-quality/)
350. [**One Embedder, Any Task: Instruction-Finetuned Text Embeddings**Hongjin Su, Weijia Shi, Jungo Kasai, et al.*2022 · 191 citations*](https://md.research.elamur.ai/free/en/papers/su-2022-one-embedder-any-task-instruction/)
351. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
352. [**Towards Making the Most of ChatGPT for Machine Translation**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/)
353. [**GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/)
354. [**PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization**Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.*2023 · 189 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pandalm-automatic-evaluation-benchmark-llm/)
355. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
356. [**Refusal in Language Models Is Mediated by a Single Direction**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
357. [**Adaptive Machine Translation with Large Language Models**Yasmin Moslem, Rejwanul Haque, John D. Kelleher, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/moslem-2023-adaptive-machine-translation-large-language/)
358. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
359. [**Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/)
360. [**LawBench: Benchmarking Legal Knowledge of Large Language Models**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
361. [**Multilingual Jailbreak Challenges in Large Language Models**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
362. [**OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/)
363. [**Preference Ranking Optimization for Human Alignment**Feifan Song, Bowen Yu, Minghao Li, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-preference-ranking-optimization-human-alignment/)
364. [**Large Language Models are few(1)-shot Table Reasoners**Wenhu Chen*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/)
365. [**Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models**Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/)
366. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 180 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
367. [**GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models**Archiki Prasad, Peter Hase, Xiang Zhou, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/prasad-2023-grips-gradient-free-edit-based/)
368. [**Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning**Fuxiao Liu, Kevin Lin, Linjie Li, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mitigating-hallucination-large-multi-modal/)
369. [**On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning**Omar Shaikh, Hongxin Zhang, William Held, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/shaikh-2023-second-thought-let-s-not/)
370. [**Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/)
371. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/)
372. [**Eliciting Latent Predictions from Transformers with the Tuned Lens**Nora Belrose, Igor Ostrovsky, Lev McKinney, et al.*2023 · 179 citations*](https://md.research.elamur.ai/free/en/papers/belrose-2023-eliciting-latent-predictions-transformers-tuned/)
373. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
374. [**Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/)
375. [**Effective Long-Context Scaling of Foundation Models**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
376. [**Evaluating Large Language Models: A Comprehensive Survey**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
377. [**On the Risk of Misinformation Pollution with Large Language Models**Yikang Pan, Liangming Pan, Wenhu Chen, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-risk-misinformation-pollution-large-language/)
378. [**ToolQA: A Dataset for LLM Question Answering with External Tools**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/)
379. [**Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/)
380. [**What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning**Wei Liu, Weihao Zeng, Keqing He, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-makes-good-data-alignment-comprehensive/)
381. [**Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 173 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/)
382. [**ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases**Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-toolalpaca-generalized-tool-learning-language/)
383. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 171 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
384. [**LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/)
385. [**OpenChat: Advancing Open-source Language Models with Mixed-Quality Data**Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-openchat-advancing-open-source-language/)
386. [**Do Llamas Work in English? On the Latent Language of Multilingual Transformers**Chris Wendler, Veniamin Veselovsky, Giovanni Monea, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wendler-2024-do-llamas-work-english-latent/)
387. [**Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs**Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/balloccu-2024-leak-cheat-repeat-data-contamination/)
388. [**LESS: Selecting Influential Data for Targeted Instruction Tuning**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
389. [**HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge**Haochun Wang, Chi Liu, Nuwa Xi, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-huatuo-tuning-llama-model-chinese/)
390. [**Learning to Compress Prompts with Gist Tokens**Jesse Mu, Xiang Lisa Li, Noah Goodman*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/mu-2023-learning-compress-prompts-gist-tokens/)
391. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
392. [**WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 168 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/)
393. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
394. [**Low-Resource Languages Jailbreak GPT-4**Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yong-2023-low-resource-languages-jailbreak-gpt/)
395. [**Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization**Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.*2022 · 166 citations*](https://md.research.elamur.ai/free/en/papers/ramamurthy-2022-reinforcement-learning-natural-language-processing/)
396. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
397. [**Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2023 · 165 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-adaptive-chameleon-stubborn-sloth-revealing/)
398. [**Large Language Model Unlearning**Yuanshun Yao, Xiaojun Xu, Yang Liu*2023 · 165 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-large-language-model-unlearning/)
399. [**Large Language Diffusion Models**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 164 citations*](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/)
400. [**Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/)

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