---
title: "Who cites Arthur Mensch"
description: "3,875 papers of the Elamur Research library cite the works of Arthur Mensch, found in their bibliographies · page 1 of 4 · 1–100; the most cited first."
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---
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# Who cites Arthur Mensch

4,216 citations of their works from 3,875 papers of our library (of the 140,884 whose bibliographies we read) · 320 with a page here, the most cited first · page 1 of 4 · 1–100 · [← Arthur Mensch](https://md.research.elamur.ai/free/en/authors/arthur-mensch/)

**1** [2](https://md.research.elamur.ai/free/en/authors/arthur-mensch/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/arthur-mensch/cited-by/page/3/) [4](https://md.research.elamur.ai/free/en/authors/arthur-mensch/cited-by/page/4/) [next →](https://md.research.elamur.ai/free/en/authors/arthur-mensch/cited-by/page/2/)

1. [**Survey of Hallucination in Natural Language Generation**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,947 citations*](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/)
2. [**LLaMA: Open and Efficient Foundation Language Models**Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.*2023 · 5,609 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-open-efficient-foundation-language/)
3. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
4. [**Gemini: A Family of Highly Capable Multimodal Models**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 2,951 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
5. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
6. [**PaLM: Scaling Language Modeling with Pathways**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 2,603 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/)
7. [**Improved Baselines with Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,557 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/)
8. [**Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Qingyang Wu, et al.*2023 · 2,487 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-visual-instruction-tuning/)
9. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,215 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
10. [**Scaling Instruction-Finetuned Language Models**Hyung Won Chung, Le Hou, Shayne Longpre, et al.*2022 · 2,176 citations*](https://md.research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/)
11. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,114 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
12. [**Flamingo: a Visual Language Model for Few-Shot Learning**Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.*2022 · 2,108 citations*](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)
13. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,013 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
14. [**OPT: Open Pre-trained Transformer Language Models**Susan Zhang, Stephen Roller, Naman Goyal, et al.*2022 · 1,709 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-opt-open-pre-trained-transformer/)
15. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,695 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
16. [**Qwen Technical Report**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,643 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
17. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
18. [**DINOv2: Learning Robust Visual Features without Supervision**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,425 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
19. [**LAION-5B: An open large-scale dataset for training next generation image-text models**Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.*2022 · 1,400 citations*](https://md.research.elamur.ai/free/en/papers/schuhmann-2022-laion-5b-open-large-scale/)
20. [**Code Llama: Open Foundation Models for Code**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,399 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
21. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
22. [**The Rise and Potential of Large Language Model Based Agents: A Survey**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,262 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)
23. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
24. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,105 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
25. [**Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,094 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)
26. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,051 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
27. [**Evaluating Object Hallucination in Large Vision-Language Models**Yifan Li, Yifan Du, Kun Zhou, et al.*2023 · 986 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)
28. [**Solving Quantitative Reasoning Problems with Language Models**Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.*2022 · 973 citations*](https://md.research.elamur.ai/free/en/papers/lewkowycz-2022-solving-quantitative-reasoning-problems-language/)
29. [**PaLM 2 Technical Report**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 971 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
30. [**A Survey on In-context Learning**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 954 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/)
31. [**Qwen2.5-VL Technical Report**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 948 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
32. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
33. [**ImageBind: One Embedding Space To Bind Them All**Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, et al.*2023 · 943 citations*](https://md.research.elamur.ai/free/en/papers/girdhar-2023-imagebind-one-embedding-space-bind/)
34. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
35. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 913 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
36. [**MMBench: Is Your Multi-modal Model an All-around Player?**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 907 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/)
37. [**A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity**Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.*2023 · 866 citations*](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/)
38. [**Segment Anything**Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.*2023 · 865 citations*](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/)
39. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 819 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
40. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
41. [**GPT-NeoX-20B: An Open-Source Autoregressive Language Model**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 818 citations*](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/)
42. [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/)
43. [**Can Large Language Models Transform Computational Social Science?**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 776 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/)
44. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
45. [**Reproducible scaling laws for contrastive language-image learning**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 750 citations*](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/)
46. [**HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face**Yongliang Shen, Kaitao Song, Xu Tan, et al.*2023 · 737 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-hugginggpt-solving-ai-tasks-chatgpt/)
47. [**SGLang: Efficient Execution of Structured Language Model Programs**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 710 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/)
48. [**Crosslingual Generalization through Multitask Finetuning**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 692 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
49. [**CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society**Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.*2023 · 689 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/)
50. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 687 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
51. [**Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 684 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)
52. [**Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models**Muhammad Maaz, Hanoona Rasheed, Salman Khan, et al.*2023 · 634 citations*](https://md.research.elamur.ai/free/en/papers/maaz-2023-video-chatgpt-towards-detailed-video/)
53. [**Video-LLaVA: Learning United Visual Representation by Alignment Before Projection**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 614 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/)
54. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 590 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
55. [**s1: Simple test-time scaling**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 584 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/)
56. [**Improving Factuality and Reasoning in Language Models through Multiagent Debate**Yilun Du, Shuang Li, Antonio Torralba, et al.*2023 · 564 citations*](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/)
57. [**Galactica: A Large Language Model for Science**Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.*2022 · 558 citations*](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/)
58. [**Precise Zero-Shot Dense Retrieval without Relevance Labels**Luyu Gao, Xueguang Ma, Jimmy Lin, et al.*2022 · 545 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-precise-zero-shot-dense-retrieval/)
59. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
60. [**Jailbreaking Black Box Large Language Models in Twenty Queries**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 533 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
61. [**How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/)
62. [**MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 529 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/)
63. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 524 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
64. [**Instruction Tuning for Large Language Models: A Survey**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 515 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/)
65. [**Baichuan 2: Open Large-scale Language Models**Aiyuan Yang, Bin Xiao, Bingning Wang, et al.*2023 · 512 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-baichuan-2-open-large-scale/)
66. [**REPLUG: Retrieval-Augmented Black-Box Language Models**Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.*2023 · 482 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/)
67. [**OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 448 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/)
68. [**LLM-Pruner: On the Structural Pruning of Large Language Models**Xinyin Ma, Gongfan Fang, Xinchao Wang*2023 · 447 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-llm-pruner-structural-pruning-large/)
69. [**FinGPT: Open-Source Financial Large Language Models**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
70. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
71. [**MVBench: A Comprehensive Multi-modal Video Understanding Benchmark**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/)
72. [**LLaVA-OneVision: Easy Visual Task Transfer**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 440 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
73. [**GPT-NER: Named Entity Recognition via Large Language Models**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/)
74. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
75. [**C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models**Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-c-eval-multi-level-multi/)
76. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 413 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
77. [**mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality**Qinghao Ye, Haiyang Xu, Guohai Xu, et al.*2023 · 410 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl-modularization-empowers-large/)
78. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 409 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
79. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 406 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)
80. [**The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale**Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.*2024 · 404 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/)
81. [**AgentBench: Evaluating LLMs as Agents**Xiao Liu, Hao Yu, Hanchen Zhang, et al.*2023 · 404 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-agentbench-evaluating-llms-agents/)
82. [**Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 403 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/)
83. [**Yi: Open Foundation Models by 01.AI**Alex Young, Bei Chen, Chao Li, et al.*2024 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
84. [**Tool Learning with Foundation Models**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 376 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/)
85. [**Editing Models with Task Arithmetic**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 374 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
86. [**CogVLM: Visual Expert for Pretrained Language Models**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 373 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/)
87. [**Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations**Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/)
88. [**VILA: On Pre-training for Visual Language Models**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 367 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/)
89. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
90. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 366 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
91. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 362 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
92. [**Augmented Language Models: a Survey**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 362 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
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