mlsanityData to 7 Oct 2026

GPT-4o System Card

arXiv 2410.21276 ↗First posted 25 Oct 2024cs.CL cs.AI cs.CVcited by 4,467

Not on the map. Why?

Cited by 1,413 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.

Key facts. Cited by 4,467 papers in the map (data through 7 Oct 2026). Builds on 21 of its 56 references that are in the map. First posted on arXiv 25 Oct 2024.

Builds on

21 of 56 references.

References · 21

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
  3. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  4. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 630
  5. 2023Towards Expert-Level Medical Question Answering with Large Language Modelscited by 382
  6. 2023Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicinecited by 319
  7. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 244
  8. 2019A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cyclecited by 192
  9. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 174
  10. 2021Understanding the Capabilities, Limitations, and Societal Impact of Large Language Modelscited by 159
  11. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
  12. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
9 more
  1. 2024LAB-Bench: Measuring Capabilities of Language Models for Biology Researchcited by 138
  2. 2022Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reductioncited by 137
  3. 2023Evaluating and Mitigating Discrimination in Language Model Decisionscited by 117
  4. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  5. 2024SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysiscited by 40
  6. 2024AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligencecited by 36
  7. 2023The Dark Side of ChatGPT: Legal and Ethical Challenges from Stochastic Parrots and Hallucinationcited by 23
  8. 2023Warning: Humans Cannot Reliably Detect Speech Deepfakescited by 20
  9. 2024Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern?cited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 98; 2025: 2570; 2026: 1799.

4,467 papers.

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  1. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
  2. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,419
  3. 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,258
  4. 2025Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Modelscited by 1,175
  5. 2024Tulu 3: Pushing Frontiers in Open Language Model Post-Trainingcited by 988
  6. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
  7. 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memorycited by 722
  8. 2025Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Modelscited by 653
  9. 2025Flow-GRPO: Training Flow Matching Models via Online RLcited by 605
  10. 2025UI-TARS: Pioneering Automated GUI Interaction with Native Agentscited by 584
  11. 2024Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spacescited by 580
  12. 2025SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wildcited by 505
38 more
  1. 2025Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAscited by 491
  2. 2025Video-R1: Reinforcing Video Reasoning in MLLMscited by 464
  3. 2024LLaVA-CoT: Let Vision Language Models Reason Step-by-Stepcited by 446
  4. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 405
  5. 2025The Lessons of Developing Process Reward Models in Mathematical Reasoningcited by 402
  6. 2025LLMs Get Lost In Multi-Turn Conversationcited by 400
  7. 2025HealthBench: Evaluating Large Language Models Towards Improved Human Healthcited by 385
  8. 2025Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscationcited by 338
  9. 2025Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domainscited by 328
  10. 2025WebThinker: Empowering Large Reasoning Models with Deep Research Capabilitycited by 320
  11. 2024Alignment faking in large language modelscited by 316
  12. 2025VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learningcited by 315
  13. 2025R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimizationcited by 296
  14. 2025MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learningcited by 294
  15. 2024CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Modelscited by 282
  16. 2024ProcessBench: Identifying Process Errors in Mathematical Reasoningcited by 277
  17. 2025Pixel Reasoner: Incentivizing Pixel-Space Reasoning with Curiosity-Driven Reinforcement Learningcited by 267
  18. 2025SWE-smith: Scaling Data for Software Engineering Agentscited by 255
  19. 2025OmniGen2: Towards Instruction-Aligned Multimodal Generationcited by 241
  20. 2024Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimizationcited by 238
  21. 2025Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactionscited by 236
  22. 2025MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agentscited by 226
  23. 2026Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Rankingcited by 211
  24. 2025Kimi-Audio Technical Reportcited by 210
  25. 2025Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligencecited by 206
  26. 2025Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergycited by 204
  27. 2025ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Drivingcited by 190
  28. 2025Mobile-Agent-v3: Fundamental Agents for GUI Automationcited by 183
  29. 2025World Simulation with Video Foundation Models for Physical AIcited by 183
  30. 2025Multimodal Chain-of-Thought Reasoning: A Comprehensive Surveycited by 176
  31. 2025MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMscited by 172
  32. 2025MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learningcited by 172
  33. 2024Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Searchcited by 171
  34. 2025Agentic Reinforced Policy Optimizationcited by 166
  35. 2025Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scalecited by 163
  36. 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
  37. 2025VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstructioncited by 154
  38. 2025LLaDA2.0: Scaling Up Diffusion Language Models to 100Bcited by 154

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