mlsanityData to 7 Oct 2026

Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

arXiv 2501.17811 ↗First posted 29 Jan 2025cs.AI cs.CL cs.CVcited by 787

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Cited by 205 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this work, we introduce Janus-Pro, an advanced version of the previous work Janus. Specifically, Janus-Pro incorporates (1) an optimized training strategy, (2) expanded training data, and (3) scaling to larger model size. With these improvements, Janus-Pro achieves significant advancements in both multimodal understanding and text-to-image instruction-following capabilities, while also enhancing the stability of text-to-image generation. We hope this work will inspire further exploration in the field. Code and models are publicly available.

Key facts. Cited by 787 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jan 2025.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 411; 2026: 376.

787 papers.

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  1. 2025Qwen-Image Technical Reportcited by 973
  2. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 855
  3. 2025Flow-GRPO: Training Flow Matching Models via Online RLcited by 605
  4. 2025WorldVLA: Towards Autoregressive Action World Modelcited by 351
  5. 2025Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformercited by 247
  6. 2025LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RLcited by 244
  7. 2025Show-o2: Improved Native Unified Multimodal Modelscited by 242
  8. 2025MMaDA: Multimodal Large Diffusion Language Modelscited by 241
  9. 2025OmniGen2: Towards Instruction-Aligned Multimodal Generationcited by 241
  10. 2025Transfer between Modalities with MetaQueriescited by 231
  11. 2025WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generationcited by 196
  12. 2025Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontierscited by 193
38 more
  1. 2025T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoTcited by 162
  2. 2025LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuningcited by 145
  3. 2025HunyuanImage 3.0 Technical Reportcited by 138
  4. 2026Cosmos 3: Omnimodal World Models for Physical AIcited by 137
  5. 2025Emu3.5: Native Multimodal Models are World Learnerscited by 119
  6. 2025Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generationcited by 108
  7. 2025X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Againcited by 105
  8. 2025Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generationcited by 95
  9. 2025ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generationcited by 94
  10. 2025TempFlow-GRPO: When Timing Matters for GRPO in Flow Modelscited by 93
  11. 2025LongCat-Image Technical Reportcited by 92
  12. 2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Modelscited by 89
  13. 2025Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learningcited by 88
  14. 2025NoisyRollout: Reinforcing Visual Reasoning with Data Augmentationcited by 86
  15. 2025SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RLcited by 85
  16. 2025Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generationcited by 84
  17. 2025Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understandingcited by 83
  18. 2025Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunitiescited by 81
  19. 2025OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generationcited by 81
  20. 2025Harmonizing Visual Representations for Unified Multimodal Understanding and Generationcited by 74
  21. 2025MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflowcited by 71
  22. 2025A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluationscited by 66
  23. 2025Ovis-U1 Technical Reportcited by 65
  24. 2025TIIF-Bench: How Does Your T2I Model Follow Your Instructions?cited by 64
  25. 2025UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generationcited by 64
  26. 2025GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generationcited by 57
  27. 2025GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generationcited by 55
  28. 2025UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokenscited by 55
  29. 2025NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scalecited by 55
  30. 2025ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinementcited by 53
  31. 2025Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Modelcited by 52
  32. 2025Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Visioncited by 52
  33. 2025Unified Autoregressive Visual Generation and Understanding with Continuous Tokenscited by 51
  34. 2025GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learningcited by 51
  35. 2025TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generationcited by 50
  36. 2025OneCAT: Decoder-Only Auto-Regressive Model for Unified Understanding and Generationcited by 50
  37. 2025UniToken: Harmonizing Multimodal Understanding and Generation through Unified Visual Encodingcited by 49
  38. 2026Scaling Text-to-Image Diffusion Transformers with Representation Autoencoderscited by 49

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