---
title: "Who cites Raphael Gontijo Lopes — 476 papers of our library"
description: "476 papers of the Elamur Research library cite the works of Raphael Gontijo Lopes, found in their bibliographies · page 1 of 2 · 1–100; the…"
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---
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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](https://md.research.elamur.ai/free/en/authors/raphael-gontijo-lopes/)

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1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
3. [**Flamingo: a Visual Language Model for Few-Shot Learning arXiv:2204.14198**Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.*2022 · 2,246 citations*](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)
4. [**LAION-5B: An open large-scale dataset for training next generation image-text models arXiv:2210.08402**Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.*2022 · 1,485 citations*](https://md.research.elamur.ai/free/en/papers/schuhmann-2022-laion-5b-open-large-scale/)
5. **[Vision-Language Models for Vision Tasks: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-vision-language-models-vision-tasks/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Jingyi Zhang, Jiaxing Huang, Sheng Jin, et al.*2023 · 1,047 citations*
6. **[Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 814 citations*
7. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 780 citations*
8. **[Reproducible scaling laws for contrastive language-image learning](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 769 citations*
9. [**CoCa: Contrastive Captioners are Image-Text Foundation Models arXiv:2205.01917**Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.*2022 · 667 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/)
10. [**Large Language Models Can Be Easily Distracted by Irrelevant Context arXiv:2302.00093**Freda Shi, Xinyun Chen, Kanishka Misra, et al.*2023 · 534 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-large-language-models-easily-distracted/)
11. [**Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time arXiv:2203.05482**Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.*2022 · 507 citations*](https://md.research.elamur.ai/free/en/papers/wortsman-2022-model-soups-averaging-weights-multiple/)
12. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
13. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
14. [**Editing Models with Task Arithmetic arXiv:2212.04089**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
15. **[Decomposed Prompting: A Modular Approach for Solving Complex Tasks](https://md.research.elamur.ai/free/en/papers/khot-2022-decomposed-prompting-modular-approach/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Tushar Khot, Harsh Trivedi, Matthew Finlayson, et al.*2023 · 390 citations*
16. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
17. [**Improving alignment of dialogue agents via targeted human judgements arXiv:2209.14375**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 362 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
18. [**Solving math word problems with process- and outcome-based feedback arXiv:2211.14275**Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.*2022 · 355 citations*](https://md.research.elamur.ai/free/en/papers/uesato-2022-solving-math-word-problems-process/)
19. **[TIES-Merging: Resolving Interference When Merging Models](https://md.research.elamur.ai/free/en/papers/yadav-2023-ties-merging-resolving-interference-merging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Prateek Yadav, Derek Tam, Leshem Choshen, et al.*2023 · 324 citations*
20. [**PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts arXiv:2306.04528**Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.*2023 · 305 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-promptrobust-towards-evaluating-robustness-large/)
21. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
22. [**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/)
23. **[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*
24. [**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/)
25. [**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/)
26. [**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/)
27. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch arXiv:2311.03099**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
28. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 208 citations*
29. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
30. **[AudioCaps: Generating Captions for Audios in The Wild](https://md.research.elamur.ai/free/en/papers/kim-2019-audiocaps-generating-captions-audios-wild/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/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 Provers](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 172 citations*
32. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
33. [**Generating Sequences by Learning to Self-Correct arXiv:2211.00053**Sean Welleck, Ximing Lu, Peter West, et al.*2022 · 172 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2022-generating-sequences-learning-self-correct/)
34. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
35. [**InternVideo: General Video Foundation Models via Generative and Discriminative Learning arXiv:2212.03191**Yi Wang, Kunchang Li, Yizhuo Li, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-internvideo-general-video-foundation/)
36. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
37. **[AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning](https://md.research.elamur.ai/free/en/papers/wang-2022-adamix-mixture-adaptations-parameter-efficient/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.*2022 · 135 citations*
38. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
39. [**Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents arXiv:2306.03314**Yashar Talebirad, Amirhossein Nadiri*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/talebirad-2023-multi-agent-collaboration-harnessing-power/)
40. [**PEER: A Collaborative Language Model arXiv:2208.11663**Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/schick-2022-peer-collaborative-language-model/)
41. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
42. [**Large Language Models as Tool Makers arXiv:2305.17126**Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/cai-2023-large-language-models-tool-makers/)
43. [**Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models arXiv:2208.03306**Margaret Li, Suchin Gururangan, Tim Dettmers, et al.*2022 · 114 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-branch-train-merge-embarrassingly-parallel/)
44. [**Arcee's MergeKit: A Toolkit for Merging Large Language Models arXiv:2403.13257**Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/goddard-2024-arcee-s-mergekit-toolkit-merging/)
45. [**Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging arXiv:2310.11564**Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-personalized-soups-personalized-large-language/)
46. [**Dataless Knowledge Fusion by Merging Weights of Language Models arXiv:2212.09849**Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, et al.*2022 · 101 citations*](https://md.research.elamur.ai/free/en/papers/jin-2022-dataless-knowledge-fusion-merging-weights/)
47. **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 99 citations*
48. [**The Platonic Representation Hypothesis arXiv:2405.07987**Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/huh-2024-platonic-representation-hypothesis/)
49. **[Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards](https://md.research.elamur.ai/free/en/papers/rame-2023-rewarded-soups-towards-pareto-optimal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.*2023 · 90 citations*
50. **[ADaPT: As-Needed Decomposition and Planning with Language Models](https://md.research.elamur.ai/free/en/papers/prasad-2024-adapt-as-needed-decomposition-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Archiki Prasad, Alexander Koller, Mareike Hartmann, et al.*2024 · 89 citations*
51. **[RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs](https://md.research.elamur.ai/free/en/papers/akyurek-2023-rl4f-generating-natural-language-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.*2023 · 89 citations*
52. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
53. [**Knowledge Fusion of Large Language Models arXiv:2401.10491**Fanqi Wan, Xinting Huang, Deng Cai, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wan-2024-knowledge-fusion-large-language-models/)
54. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
55. [**Branch-Solve-Merge Improves Large Language Model Evaluation and Generation arXiv:2310.15123**Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/saha-2023-branch-solve-merge-improves-large/)
56. [**Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction arXiv:2508.03613**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-v2-scaling-formal/)
57. **[On the Effects of Data Scale on UI Control Agents](https://md.research.elamur.ai/free/en/papers/li-2024-effects-data-scale-ui-control/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Li, William Bishop, Alice Li, et al.*2024 · 67 citations*
58. [**Exploring the Benefits of Training Expert Language Models over Instruction Tuning arXiv:2302.03202**Joel Jang, Seungone Kim, Seonghyeon Ye, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-exploring-benefits-training-expert-language/)
59. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
60. **[Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic](https://md.research.elamur.ai/free/en/papers/bhardwaj-2024-language-models-are-homer-simpson/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria*2024 · 59 citations*
61. [**AdaMerging: Adaptive Model Merging for Multi-Task Learning arXiv:2310.02575**Enneng Yang, Zhenyi Wang, Li Shen, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/)
62. **[Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions](https://md.research.elamur.ai/free/en/papers/zelikman-2023-parsel-algorithmic-reasoning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Eric Zelikman, Qian Huang, Gabriel Poesia, et al.*2023 · 56 citations*
63. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
64. [**Gemini Embedding: Generalizable Embeddings from Gemini arXiv:2503.07891**Jinhyuk Lee, Feiyang Chen, Sahil Dua, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/lee-2025-gemini-embedding-generalizable-embeddings-gemini/)
65. **[Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts](https://md.research.elamur.ai/free/en/papers/tan-2024-personalized-pieces-efficient-personalized-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoxuan Tan, Zheyuan Liu, Meng Jiang*2024 · 40 citations*
66. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
67. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
68. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
69. [**Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models arXiv:2305.09955**Shangbin Feng, Weijia Shi, Yuyang Bai, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-knowledge-card-filling-llms-knowledge/)
70. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 31 citations*
71. **[FuseChat: Knowledge Fusion of Chat Models](https://md.research.elamur.ai/free/en/papers/wan-2025-fusechat-knowledge-fusion-chat-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.*2025 · 25 citations*
72. [**StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows arXiv:2403.11322**Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-stateflow-enhancing-llm-task-solving/)
73. **[Joint Prompt Optimization of Stacked LLMs using Variational Inference](https://md.research.elamur.ai/free/en/papers/sordoni-2023-joint-prompt-optimization-stacked-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.*2023 · 23 citations*
74. [**Memory Augmented Large Language Models are Computationally Universal arXiv:2301.04589**Dale Schuurmans*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/schuurmans-2023-memory-augmented-large-language-models/)
75. [**StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements**Jillian Fisher, Skyler Hallinan, Ximing Lu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/fisher-2024-styleremix-interpretable-authorship-obfuscation-distillation/)
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77. [**Fanar 2.0: Arabic Generative AI Stack arXiv:2603.16397**FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.*2026 · 11 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-fanar-2-0-arabic-generative/)
78. **[Grounding Multilingual Multimodal LLMs With Cultural Knowledge](https://md.research.elamur.ai/free/en/papers/nyandwi-2025-grounding-multilingual-multimodal-llms-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.*2025 · 11 citations*
79. **[Multi-Attribute Steering of Language Models via Targeted Intervention](https://md.research.elamur.ai/free/en/papers/nguyen-2025-multi-attribute-steering-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.*2025 · 11 citations*
80. **[Nature-Inspired Population-Based Evolution of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-nature-inspired-population-based-evolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.*2026 · 8 citations*
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82. **[Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/szep-2026-fine-tuning-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.*2026 · 7 citations*
83. [**TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation arXiv:2503.04872**Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-tinyr1-32b-preview-boosting-accuracy/)
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88. [**Family Matters: Language Transfer and Merging for Adapting Small LLMs to Faroese arXiv:2510.00810**Jenny Kunz, Iben Nyholm Debess, Annika Simonsen*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/kunz-2025-family-matters-language-transfer-merging/)
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