mlsanityData to 7 Oct 2026

PC Agent: While You Sleep, AI Works -- A Cognitive Journey into Digital World

arXiv 2412.17589 ↗First posted 23 Dec 2024cs.AI cs.LGcited by 12

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Abstract (arXiv)

Imagine a world where AI can handle your work while you sleep - organizing your research materials, drafting a report, or creating a presentation you need for tomorrow. However, while current digital agents can perform simple tasks, they are far from capable of handling the complex real-world work that humans routinely perform. We present PC Agent, an AI system that demonstrates a crucial step toward this vision through human cognition transfer. Our key insight is that the path from executing simple "tasks" to handling complex "work" lies in efficiently capturing and learning from human cognitive processes during computer use. To validate this hypothesis, we introduce three key innovations: (1) PC Tracker, a lightweight infrastructure that efficiently collects high-quality human-computer interaction trajectories with complete cognitive context; (2) a two-stage cognition completion pipeline that transforms raw interaction data into rich cognitive trajectories by completing action semantics and thought processes; and (3) a multi-agent system combining a planning agent for decision-making with a grounding agent for robust visual grounding. Our preliminary experiments in PowerPoint presentation creation reveal that complex digital work capabilities can be achieved with a small amount of high-quality cognitive data - PC Agent, trained on just 133 cognitive trajectories, can handle sophisticated work scenarios involving up to 50 steps across multiple applications. This demonstrates the data efficiency of our approach, highlighting that the key to training capable digital agents lies in collecting human cognitive data. By open-sourcing our complete framework, including the data collection infrastructure and cognition completion methods, we aim to lower the barriers for the research community to develop truly capable digital agents.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 25 of its 43 references that are in the map. First posted on arXiv 23 Dec 2024.

Builds on

25 of 43 references.

References · 25

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  3. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,310
  4. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
  5. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  6. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  7. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
  8. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
  9. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
  10. 2023CogAgent: A Visual Language Model for GUI Agentscited by 692
  11. 2024SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agentscited by 553
  12. 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 547
13 more
  1. 2023AppAgent: Multimodal Agents as Smartphone Userscited by 407
  2. 2024Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agentscited by 373
  3. 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agentscited by 370
  4. 2024AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agentscited by 359
  5. 2023A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesiscited by 350
  6. 2024Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scalecited by 212
  7. 2024OmniParser for Pure Vision Based GUI Agentcited by 193
  8. 2023You Only Look at Screens: Multimodal Chain-of-Action Agentscited by 185
  9. 2024Agent S: An Open Agentic Framework that Uses Computers Like a Humancited by 182
  10. 2024Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMscited by 173
  11. 2024Android in the Zoo: Chain-of-Action-Thought for GUI Agentscited by 156
  12. 2024The Dawn of GUI Agent: A Preliminary Case Study with Claude 3.5 Computer Usecited by 62
  13. 2024AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistantcited by 27

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 4.

12 papers.