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Who cites Raphael Gontijo Lopes

520 citations of their works from 476 papers of our library (of the 149,439 whose bibliographies we read) · 105 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Raphael Gontijo Lopes

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  1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  2. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  3. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  4. LAION-5B: An open large-scale dataset for training next generation image-text modelsarXiv:2210.08402Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.2022 · 1,485 citations
  5. Vision-Language Models for Vision Tasks: A SurveyIEEE Transactions on Pattern Analysis and Machine IntelligenceJingyi Zhang, Jiaxing Huang, Sheng Jin, et al.2023 · 1,047 citations
  6. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  7. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
  8. Reproducible scaling laws for contrastive language-image learningIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMehdi Cherti, Romain Beaumont, Ross Wightman, et al.2022 · 769 citations
  9. CoCa: Contrastive Captioners are Image-Text Foundation ModelsarXiv:2205.01917Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.2022 · 667 citations
  10. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  11. Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timearXiv:2203.05482Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.2022 · 507 citations
  12. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  13. BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsFindings of the Association for Computational LinguisticsYanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.2024 · 409 citations
  14. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  15. Decomposed Prompting: A Modular Approach for Solving Complex TasksInternational Conference on Learning Representations (ICLR)Tushar Khot, Harsh Trivedi, Matthew Finlayson, et al.2023 · 390 citations
  16. PaLI: A Jointly-Scaled Multilingual Language-Image ModelarXiv:2209.06794Xi Chen, Xiao Wang, Soravit Changpinyo, et al.2022 · 371 citations
  17. Improving alignment of dialogue agents via targeted human judgementsarXiv:2209.14375Amelia Glaese, Nat McAleese, Maja Trębacz, et al.2022 · 362 citations
  18. Solving math word problems with process- and outcome-based feedbackarXiv:2211.14275Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.2022 · 355 citations
  19. TIES-Merging: Resolving Interference When Merging ModelsConference on Neural Information Processing Systems (NeurIPS)Prateek Yadav, Derek Tam, Leshem Choshen, et al.2023 · 324 citations
  20. PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial PromptsarXiv:2306.04528Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.2023 · 305 citations
  21. Socratic Models: Composing Zero-Shot Multimodal Reasoning with LanguagearXiv:2204.00598Andy Zeng, Maria Attarian, Brian Ichter, et al.2022 · 302 citations
  22. DSPy: Compiling Declarative Language Model Calls into Self-Improving PipelinesarXiv:2310.03714Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.2023 · 285 citations
  23. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  24. Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtarXiv:2210.01240Abulhair Saparov, He He2022 · 244 citations
  25. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
  26. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  27. Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LuncharXiv:2311.03099Le Yu, Bowen Yu, Haiyang Yu, et al.2023 · 217 citations
  28. Merging Models with Fisher-Weighted AveragingConference on Neural Information Processing Systems (NeurIPS)Michael Matena, Colin Raffel2021 · 208 citations
  29. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  30. AudioCaps: Generating Captions for Audios in The WildConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, et al.2019 · 187 citations
  31. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 172 citations
  32. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
  33. Generating Sequences by Learning to Self-CorrectarXiv:2211.00053Sean Welleck, Ximing Lu, Peter West, et al.2022 · 172 citations
  34. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  35. InternVideo: General Video Foundation Models via Generative and Discriminative LearningarXiv:2212.03191Yi Wang, Kunchang Li, Yizhuo Li, et al.2022 · 144 citations
  36. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  37. AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.2022 · 135 citations
  38. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  39. Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM AgentsarXiv:2306.03314Yashar Talebirad, Amirhossein Nadiri2023 · 130 citations
  40. PEER: A Collaborative Language ModelarXiv:2208.11663Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.2022 · 126 citations
  41. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
  42. Large Language Models as Tool MakersarXiv:2305.17126Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.2023 · 123 citations
  43. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language ModelsarXiv:2208.03306Margaret Li, Suchin Gururangan, Tim Dettmers, et al.2022 · 114 citations
  44. Arcee's MergeKit: A Toolkit for Merging Large Language ModelsarXiv:2403.13257Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.2024 · 105 citations
  45. Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingarXiv:2310.11564Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.2023 · 102 citations
  46. Dataless Knowledge Fusion by Merging Weights of Language ModelsarXiv:2212.09849Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, et al.2022 · 101 citations
  47. Optimizing Instructions and Demonstrations for Multi-Stage Language Model ProgramsConference on Empirical Methods in Natural Language Processing (EMNLP)Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.2024 · 99 citations
  48. The Platonic Representation HypothesisarXiv:2405.07987Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.2024 · 96 citations
  49. Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewardsConference on Neural Information Processing Systems (NeurIPS)Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.2023 · 90 citations
  50. ADaPT: As-Needed Decomposition and Planning with Language ModelsFindings of the Association for Computational LinguisticsArchiki Prasad, Alexander Koller, Mareike Hartmann, et al.2024 · 89 citations
  51. RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model OutputsAnnual Meeting of the Association for Computational Linguistics (ACL)Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.2023 · 89 citations
  52. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
  53. Knowledge Fusion of Large Language ModelsarXiv:2401.10491Fanqi Wan, Xinting Huang, Deng Cai, et al.2024 · 82 citations
  54. Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and OpportunitiesarXiv:2408.07666Enneng Yang, Li Shen, Guibing Guo, et al.2024 · 79 citations
  55. Branch-Solve-Merge Improves Large Language Model Evaluation and GenerationarXiv:2310.15123Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.2023 · 68 citations
  56. Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-CorrectionarXiv:2508.03613Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 67 citations
  57. On the Effects of Data Scale on UI Control AgentsConference on Neural Information Processing Systems (NeurIPS)Wei Li, William Bishop, Alice Li, et al.2024 · 67 citations
  58. Exploring the Benefits of Training Expert Language Models over Instruction TuningarXiv:2302.03202Joel Jang, Seungone Kim, Seonghyeon Ye, et al.2023 · 63 citations
  59. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
  60. Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticAnnual Meeting of the Association for Computational Linguistics (ACL)Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria2024 · 59 citations
  61. AdaMerging: Adaptive Model Merging for Multi-Task LearningarXiv:2310.02575Enneng Yang, Zhenyi Wang, Li Shen, et al.2023 · 59 citations
  62. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
  63. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  64. Gemini Embedding: Generalizable Embeddings from GeminiarXiv:2503.07891Jinhyuk Lee, Feiyang Chen, Sahil Dua, et al.2025 · 45 citations
  65. Personalized Pieces: Efficient Personalized Large Language Models through Collaborative EffortsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhaoxuan Tan, Zheyuan Liu, Meng Jiang2024 · 40 citations
  66. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
  67. Aligning Language Models with Preferences through f-divergence MinimizationarXiv:2302.08215Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.2023 · 39 citations
  68. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
  69. Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language ModelsarXiv:2305.09955Shangbin Feng, Weijia Shi, Yuyang Bai, et al.2023 · 35 citations
  70. Scaling Laws and Compute-Optimal Training Beyond Fixed Training DurationsConference on Neural Information Processing Systems (NeurIPS)Alexander Hägele, Elie Bakouch, Atli Kosson, et al.2024 · 31 citations
  71. FuseChat: Knowledge Fusion of Chat ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.2025 · 25 citations
  72. StateFlow: Enhancing LLM Task-Solving through State-Driven WorkflowsarXiv:2403.11322Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.2024 · 25 citations
  73. Joint Prompt Optimization of Stacked LLMs using Variational InferenceConference on Neural Information Processing Systems (NeurIPS)Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.2023 · 23 citations
  74. Memory Augmented Large Language Models are Computationally UniversalarXiv:2301.04589Dale Schuurmans2023 · 19 citations
  75. StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style ElementsJillian Fisher, Skyler Hallinan, Ximing Lu, et al.2024 · 16 citations
  76. Value Profiles for Encoding Human VariationConference on Empirical Methods in Natural Language Processing (EMNLP)Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.2025 · 15 citations
  77. Fanar 2.0: Arabic Generative AI StackarXiv:2603.16397FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.2026 · 11 citations
  78. Grounding Multilingual Multimodal LLMs With Cultural KnowledgeConference on Empirical Methods in Natural Language Processing (EMNLP)Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.2025 · 11 citations
  79. Multi-Attribute Steering of Language Models via Targeted InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.2025 · 11 citations
  80. Nature-Inspired Population-Based Evolution of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.2026 · 8 citations
  81. Cool-Fusion: Fuse Large Language Models without TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Cong Liu, Xiaojun Quan, Yan Pan, et al.2025 · 8 citations
  82. Fine-tuning Large Language Models with Limited Data: A Survey and Practical GuideTransactions of the Association for Computational Linguistics (TACL)Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.2026 · 7 citations
  83. TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge DistillationarXiv:2503.04872Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.2025 · 7 citations
  84. LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-DisjointAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Ma, Dongrui Liu, Qian Chen, et al.2025 · 5 citations
  85. Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded UpdatesAnnual Meeting of the Association for Computational Linguistics (ACL)Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, et al.2026 · 3 citations
  86. K-Merge: Online Continual Merging of Adapters for On-device Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Donald Shenaj, Ondrej Bohdal, Taha Ceritli, et al.2026 · 2 citations
  87. Why Do More Experts Fail? A Theoretical Analysis of Model MergingAnnual Meeting of the Association for Computational Linguistics (ACL)Zijing Wang, Xingle Xu, YongKang Liu, et al.2026 · 2 citations
  88. Family Matters: Language Transfer and Merging for Adapting Small LLMs to FaroesearXiv:2510.00810Jenny Kunz, Iben Nyholm Debess, Annika Simonsen2025 · 2 citations
  89. Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.2026 · 1 citation
  90. Building LLMs Like LEGO: Two-dimensional Architecture Reassembly of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xingyu Wu, Yu Zhou, KC Tan2026 · 1 citation
  91. H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Selim Furkan Tekin, Fatih Ilhan, Sihao Hu, et al.2026 · 1 citation
  92. A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAMΔ Integration into Upcycled MoEAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Zhou, Tianhao Li, Zhijun Wang, et al.2026
  93. Accelerating LLM Fine-Tuning via Embedding Knowledge TransferFindings of the Association for Computational LinguisticsMeishu Peng, Ziyue Zhang, Yi Zhang, et al.2026
  94. Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual LearningFindings of the Association for Computational LinguisticsZheng Wu, Xingyu Lou, Xinbei Ma, et al.2026
  95. Component Transfer Can Exceed Full Model Performance: Investigating Post-Trained Mixture-of-ExpertsWorkshop on Generation, Evaluation and Metrics (GEM)Rabin Tiwari2026
  96. Data Pollination: An Emergent Ecological Process Driving AI Population EvolutionAnnual Meeting of the Association for Computational Linguistics (ACL)Shufang Xie, Qizhi Pei, Ang Lv, et al.2026
  97. DivMerge: A divergence-based model merging method for multi-taskingConference of the European Chapter of the Association for Computational Linguistics (EACL)Brahim Touayouch, Loïc Fosse, Géraldine Damnati, et al.2026
  98. From Atomic to Complex tasks: Cross-Tasking Improves Zero-Shot Argument Generation and RetrievalFindings of the Association for Computational LinguisticsLynda Tamine, Ahmed Rayane Kebir, Merveille Dona Codjo, et al.2026
  99. GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiwen Ruan, Yichao Du, Jianjie Zheng, et al.2026
  100. GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy InputsFindings of the Association for Computational LinguisticsZhengxin Zhang, Chengyu Huang, Xufu Liu, et al.2026

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