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Who cites Ce Liu

1,445 citations of their works from 1,419 papers of our library (of the 149,439 whose bibliographies we read) · 273 with a page here, the most cited first · page 1 of 3 · 1–100 · ← Ce Liu

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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. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  3. Scalable Diffusion Models with TransformersIEEE/CVF International Conference on Computer Vision (ICCV)William Peebles, Saining Xie2022 · 2,670 citations
  4. Visual Instruction TuningarXiv:2304.08485Haotian Liu, Chunyuan Li, Qingyang Wu, et al.2023 · 2,617 citations
  5. Revisiting Unreasonable Effectiveness of Data in Deep Learning EraIEEE International Conference on Computer Vision (ICCV)Chen Sun, Abhinav Shrivastava, Saurabh Singh, et al.2017 · 2,512 citations
  6. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  7. MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language ModelsarXiv:2304.10592Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.2023 · 1,141 citations
  8. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
  9. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
  10. LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.2024 · 1,048 citations
  11. 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
  12. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
  13. Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields ReconstructionIEEE Computer Society Conference on Computer Vision and Pattern RecognitionCheng Sun, Min Sun, Hwann-Tzong Chen2021 · 1,016 citations
  14. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations
  15. CoCa: Contrastive Captioners are Image-Text Foundation ModelsarXiv:2205.01917Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.2022 · 667 citations
  16. Video-LLaVA: Learning United Visual Representation by Alignment Before ProjectionConference on Empirical Methods in Natural Language Processing (EMNLP)Bin Lin, Yang Ye, Bin Zhu, et al.2023 · 627 citations
  17. MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.2023 · 554 citations
  18. Phi-4 Technical ReportarXiv:2412.08905Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.2024 · 502 citations
  19. InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic TasksarXiv:2312.14238Zhe Chen, Jiannan Wu, Wenhai Wang, et al.2023 · 435 citations
  20. The FineWeb Datasets: Decanting the Web for the Finest Text Data at ScaleConference on Neural Information Processing Systems (NeurIPS)Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.2024 · 434 citations
  21. mPLUG-Owl: Modularization Empowers Large Language Models with MultimodalityarXiv:2304.14178Qinghao Ye, Haiyang Xu, Guohai Xu, et al.2023 · 427 citations
  22. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 400 citations
  23. CogVLM: Visual Expert for Pretrained Language ModelsConference on Neural Information Processing Systems (NeurIPS)Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.2023 · 383 citations
  24. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  25. PaLI: A Jointly-Scaled Multilingual Language-Image ModelarXiv:2209.06794Xi Chen, Xiao Wang, Soravit Changpinyo, et al.2022 · 371 citations
  26. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  27. VideoChat: Chat-Centric Video UnderstandingScience China Information SciencesKunChang Li, Yinan He, Yi Wang, et al.2023 · 365 citations
  28. MM-Vet: Evaluating Large Multimodal Models for Integrated CapabilitiesarXiv:2308.02490Weihao Yu, Zhengyuan Yang, Linjie Li, et al.2023 · 344 citations
  29. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
  30. Language Is Not All You Need: Aligning Perception with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Shaohan Huang, Li Dong, Wenhui Wang, et al.2023 · 330 citations
  31. Chameleon: Plug-and-Play Compositional Reasoning with Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Pan Lu, Baolin Peng, Hao Cheng, et al.2023 · 327 citations
  32. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
  33. The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)arXiv:2309.17421Zhengyuan Yang, Linjie Li, Kevin Lin, et al.2023 · 311 citations
  34. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
  35. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  36. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
  37. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
  38. QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMsConference on Neural Information Processing Systems (NeurIPS)Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.2024 · 254 citations
  39. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  40. LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
  41. TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question AnsweringIEEE/CVF International Conference on Computer Vision (ICCV)Yushi Hu, Benlin Liu, Jungo Kasai, et al.2023 · 218 citations
  42. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
  43. ChemCrow: Augmenting large-language models with chemistry toolsarXiv:2304.05376Andres M Bran, Sam Cox, Oliver Schilter, et al.2023 · 211 citations
  44. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  45. Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicarXiv:2306.15195Keqin Chen, Zhao Zhang, Weili Zeng, et al.2023 · 210 citations
  46. NExT-GPT: Any-to-Any Multimodal LLMarXiv:2309.05519Shengqiong Wu, Hao Fei, Leigang Qu, et al.2023 · 207 citations
  47. Woodpecker: Hallucination Correction for Multimodal Large Language ModelsScience China Information SciencesShukang Yin, Chaoyou Fu, Sirui Zhao, et al.2023 · 206 citations
  48. MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse AttentionConference on Neural Information Processing Systems (NeurIPS)Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.2024 · 202 citations
  49. MM-REACT: Prompting ChatGPT for Multimodal Reasoning and ActionarXiv:2303.11381Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.2023 · 196 citations
  50. Tool Learning with Large Language Models: A SurveyFrontiers of Computer ScienceChangle Qu, Sunhao Dai, Xiaochi Wei, et al.2024 · 195 citations
  51. 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
  52. Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction TuningarXiv:2306.14565Fuxiao Liu, Kevin Lin, Linjie Li, et al.2023 · 189 citations
  53. ToolQA: A Dataset for LLM Question Answering with External ToolsConference on Neural Information Processing Systems (NeurIPS)Yuchen Zhuang, Yue Yu, Kuan Wang, et al.2023 · 182 citations
  54. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  55. Large Language Diffusion ModelsConference on Neural Information Processing Systems (NeurIPS)Shen Nie, Fengqi Zhu, Zebin You, et al.2025 · 178 citations
  56. Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved YetConference on Machine Translation (WMT)Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.2024 · 178 citations
  57. Promptbreeder: Self-Referential Self-Improvement Via Prompt EvolutionarXiv:2309.16797Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.2023 · 174 citations
  58. Scaling Synthetic Data Creation with 1,000,000,000 PersonasarXiv:2406.20094Tao Ge, Xin Chan, Xiaoyang Wang, et al.2024 · 171 citations
  59. LongVideoBench: A Benchmark for Long-context Interleaved Video-Language UnderstandingConference on Neural Information Processing Systems (NeurIPS)Haoning Wu, Dongxu Li, Bei Chen, et al.2024 · 166 citations
  60. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  61. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  62. Pix2Struct: Screenshot Parsing as Pretraining for Visual Language UnderstandingarXiv:2210.03347Kenton Lee, Mandar Joshi, Iulia Turc, et al.2022 · 158 citations
  63. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
  64. Simple and Effective Masked Diffusion Language ModelsConference on Neural Information Processing Systems (NeurIPS)Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.2024 · 152 citations
  65. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  66. GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructionConference on Neural Information Processing Systems (NeurIPS)Rui Yang, Lin Song, Yanwei Li, et al.2023 · 147 citations
  67. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
  68. InternVideo: General Video Foundation Models via Generative and Discriminative LearningarXiv:2212.03191Yi Wang, Kunchang Li, Yizhuo Li, et al.2022 · 144 citations
  69. PaliGemma: A versatile 3B VLM for transferarXiv:2407.07726Lucas Beyer, Andreas Steiner, Andre Susano Pinto, et al.2024 · 142 citations
  70. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  71. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 137 citations
  72. Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4VarXiv:2310.11441Jianwei Yang, Hao Zhang, Feng Li, et al.2023 · 137 citations
  73. 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
  74. MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding BenchmarkarXiv:2409.02813Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.2024 · 123 citations
  75. Large Language Models as Tool MakersarXiv:2305.17126Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.2023 · 123 citations
  76. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
  77. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksarXiv:2404.02151Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion2024 · 118 citations
  78. Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Hao Shao, Shengju Qian, Han Xiao, et al.2024 · 117 citations
  79. Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.2024 · 112 citations
  80. PaperQA: Retrieval-Augmented Generative Agent for Scientific ResearcharXiv:2312.07559Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.2023 · 109 citations
  81. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
  82. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
  83. A Careful Examination of Large Language Model Performance on Grade School ArithmeticConference on Neural Information Processing Systems (NeurIPS)Hugh Zhang, Jeff Da, Dean Lee, et al.2024 · 101 citations
  84. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
  85. LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive MemoryarXiv:2410.10813Di Wu, Hongwei Wang, Wenhao Yu, et al.2024 · 95 citations
  86. Small Language Models are the Future of Agentic AIarXiv:2506.02153Peter Belcak, Greg Heinrich, Shizhe Diao, et al.2025 · 92 citations
  87. Simplified and Generalized Masked Diffusion for Discrete DataConference on Neural Information Processing Systems (NeurIPS)Jiaxin Shi, Kehang Han, Zhe Wang, et al.2024 · 90 citations
  88. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
  89. BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-HaystackConference on Neural Information Processing Systems (NeurIPS)Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.2024 · 88 citations
  90. Liger Kernel: Efficient Triton Kernels for LLM TrainingarXiv:2410.10989Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.2024 · 87 citations
  91. MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction TuningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.2024 · 86 citations
  92. KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge GraphAnnual Meeting of the Association for Computational Linguistics (ACL)Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, et al.2025 · 78 citations
  93. OR-Bench: An Over-Refusal Benchmark for Large Language ModelsarXiv:2405.20947Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.2024 · 76 citations
  94. Mutual Reasoning Makes Smaller LLMs Stronger Problem-SolversarXiv:2408.06195Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.2024 · 74 citations
  95. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
  96. OffsetBias: Leveraging Debiased Data for Tuning EvaluatorsFindings of the Association for Computational LinguisticsJunsoo Park, Seungyeon Jwa, Ren Meiying, et al.2024 · 67 citations
  97. LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMsarXiv:2408.07055Yushi Bai, Jiajie Zhang, Xin Lv, et al.2024 · 66 citations
  98. Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Su, Kezhi Kong, Ying Lin, et al.2025 · 65 citations
  99. Small LLMs Are Weak Tool Learners: A Multi-LLM AgentConference on Empirical Methods in Natural Language Processing (EMNLP)Weizhou Shen, Chenliang Li, Hongzhan Chen, et al.2024 · 65 citations
  100. We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?arXiv:2407.01284Runqi Qiao, Qiuna Tan, Guanting Dong, et al.2024 · 65 citations

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