DeepSurvey: Agent-Oriented Automated Survey Generation with Analytical Depth and Citation Reliability
cs.AI
Submitted: 2026-05-28
Updated: 2026-09-29
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- SurGE: A Benchmark and Evaluation Framework for Scientific Survey Generation
- PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
- LexRank: Graph-based Lexical Centrality as Salience in Text Summarization
- MinerU: An Open-Source Solution for Precise Document Content Extraction
- LLM$\times$MapReduce-V2: Entropy-Driven Convolutional Test-Time Scaling for Generating Long-Form Articles from Extremely Long Resources
- OpenAI GPT-5 System Card
- AutoSurvey: Large Language Models Can Automatically Write Surveys
- MVSS: A Unified Framework for Multi-View Structured Survey Generation
- SurveyG: A Multi-Agent LLM Framework with Hierarchical Citation Graph for Automated Survey Generation
- Deep Literature Survey Automation with an Iterative Workflow
- LiRA: A Multi-Agent Framework for Reliable and Readable Literature Review Generation
- Agentic AutoSurvey: Let LLMs Survey LLMs
- RecurrentGPT: Interactive Generation of (Arbitrarily) Long Text
- TaxoAlign: Scholarly Taxonomy Generation Using Language Models
- Agentic AI-Empowered Dynamic Survey Framework
- SurveyForge: On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing
- Hierarchical Catalogue Generation for Literature Review: A Benchmark
- AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveys
- SurveyX: Academic Survey Automation via Large Language Models
- OUTLINEFORGE: Hierarchical Reinforcement Learning with Explicit States for Scientific Writing
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