mlsanityData to 14 Oct 2026

AI4Research: A Survey of Artificial Intelligence for Scientific Research

arXiv 2507.01903 ↗First posted 2 Jul 2025cs.CL cs.AIcited by 60

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs) such as OpenAI-o1 and DeepSeek-R1, have demonstrated remarkable capabilities in complex domains such as logical reasoning and experimental coding. Motivated by these advancements, numerous studies have explored the application of AI in the innovation process, particularly in the context of scientific research. These AI technologies primarily aim to develop systems that can autonomously conduct research processes across a wide range of scientific disciplines. Despite these significant strides, a comprehensive survey on AI for Research (AI4Research) remains absent, which hampers our understanding and impedes further development in this field. To address this gap, we present a comprehensive survey and offer a unified perspective on AI4Research. Specifically, the main contributions of our work are as follows: (1) Systematic taxonomy: We first introduce a systematic taxonomy to classify five mainstream tasks in AI4Research. (2) New frontiers: Then, we identify key research gaps and highlight promising future directions, focusing on the rigor and scalability of automated experiments, as well as the societal impact. (3) Abundant applications and resources: Finally, we compile a wealth of resources, including relevant multidisciplinary applications, data corpora, and tools. We hope our work will provide the research community with quick access to these resources and stimulate innovative breakthroughs in AI4Research.

Key facts. Cited by 60 papers in the map (data through 14 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. First posted on arXiv 2 Jul 2025.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 17; 2026: 43.

60 papers.

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  1. 2025A Survey of Context Engineering for Large Language Modelscited by 126
  2. 2025From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discoverycited by 77
  3. 2026EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discoverycited by 51
  4. 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Taskscited by 38
  5. 2025A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontierscited by 37
  6. 2025Paper2Video: Automatic Video Generation from Scientific Paperscited by 24
  7. 2025Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trendscited by 20
  8. 2025ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Modelscited by 18
  9. 2026RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvementcited by 18
  10. 2025PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraintscited by 16
  11. 2025CoDA: Agentic Systems for Collaborative Data Visualizationcited by 15
  12. 2025Jr. AI Scientist and Its Risk Report: Autonomous Scientific Exploration from a Baseline Papercited by 12
38 more
  1. 2026LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMscited by 12
  2. 2025HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Researchcited by 11
  3. 2025Scaling Generalist Data-Analytic Agentscited by 11
  4. 2026AI for Auto-Research: Roadmap & User Guidecited by 11
  5. 2026Can We Predict Before Executing Machine Learning Agents?cited by 10
  6. 2026AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discoverycited by 10
  7. 2025Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluatorcited by 9
  8. 2025Agent2World: Learning to Generate Symbolic World Models via Adaptive Multi-Agent Feedbackcited by 9
  9. 2026InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problemcited by 8
  10. 2026RebuttalAgent: Strategic Persuasion in Academic Rebuttal via Theory of Mindcited by 6
  11. 2026From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AIcited by 6
  12. 2026Beyond NL2Code: A Structured Survey of Multimodal Code Intelligencecited by 6
  13. 2026Emergent Risks in Generative Multi-Agent Systemscited by 5
  14. 2026HiRAS: A Hierarchical Multi-Agent Framework for Paper-to-Code Generation and Executioncited by 5
  15. 2026OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Modelcited by 5
  16. 2026Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysiscited by 5
  17. 2026SciIntegrity-Bench: A Benchmark for Evaluating Academic Integrity in AI Scientist Systemscited by 5
  18. 2026Let's Think with Images Efficiently! An Interleaved-Modal Chain-of-Thought Reasoning Framework with Dynamic and Precise Visual Thoughtscited by 4
  19. 2026GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responsescited by 4
  20. 2026ConvexBench: Can LLMs Recognize Convex Functions?cited by 3
  21. 2026APRES: An Agentic Paper Revision and Evaluation Systemcited by 3
  22. 2026FlowPIE: Test-Time Scientific Idea Evolution with Flow-Guided Literature Explorationcited by 3
  23. 2026The Scaling Laws of Skills in LLM Agent Systemscited by 3
  24. 2025AutoPR: Let's Automate Your Academic Promotion!cited by 2
  25. 2026When AI reviews science: Can we trust the referee?cited by 2
  26. 2026Figures as Programs: Recursive Generation of Editable Scientific Figurescited by 2
  27. 2025What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representationscited by 1
  28. 2026Structurally Human, Semantically Biased: Detecting LLM-Generated References with Embeddings and GNNscited by 1
  29. 2026Heterogeneous Scientific Foundation Model Collaborationcited by 1
  30. 2026SciAtlas: A Computable Atlas of Science for Knowledge-Grounded AI Researchcited by 1
  31. 2026Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025cited by 1
  32. 2026Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systemscited by 1
  33. 2026Can LLM design high-quality experiments? A Comprehensive and Systematic Benchmark on Autonomous Experimental Designcited by 1
  34. 2026Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender Systemcited by 1
  35. 2025AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysiscited by 0
  36. 2026OUTLINEFORGE: Hierarchical Reinforcement Learning with Explicit States for Scientific Writingcited by 0
  37. 2026From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generationcited by 0
  38. 2026Story2Proposal: A Scaffold for Structured Scientific Paper Writingcited by 0

50 most cited of 60 All 60 (JSON)

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  3. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
  4. 2025A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications
  5. 2025Agent4S: The Transformation of Research Paradigms from the Perspective of Large Language Models
  6. 2026Deep Research of Deep Research: From Transformer to Agent, From AI to AI for Science
  7. 2024Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges
  8. 2026Towards End-to-End Automation of AI Research