12,445 papers · continuously updated · last export: 10 Aug 2026livingmeta.ai
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Research theme

RAG for Research

The RAG for Research theme comprises 786 papers in this corpus published between 2006 and 2026. Work here is dominated by Design Science, Experimental, Benchmarking. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Design Science340 (43%)
  • Experimental109 (14%)
  • Benchmarking105 (13%)
  • Empirical Study100 (13%)
  • Literature Review45 (6%)
  • Case Study38 (5%)

Research domains

  • Knowledge Synthesis325 (41%)
  • Literature Discovery185 (24%)
  • Data Analysis124 (16%)
  • Scholarly Infrastructure58 (7%)
  • Human-AI Collaboration28 (4%)
  • Academic Writing10 (1%)

Frequent sub-topics

LLM-enabled transcriptomics data retrieval and gene discovery automation · 1LLM-mediated knowledge codification and tacit knowledge externalization · 1knowledge graph-augmented RAG for psychology interventions · 1knowledge graph-enhanced retrieval-augmented generation for biomedical QA · 1Anchor-guided disentanglement of embeddings for interpretable document retrieval · 1agentic_retrieval_augmented_generation_for_qa · 1retrieval-augmented generation for legal judgment prediction · 1RAG for privacy pattern design · 1

Open research gaps

  • not_available
  • The authors identify that "existing benchmarks for Generators provide limited coverage, with none enabling simultaneous evaluation of multiple capabilities under unified conditions," which motivated t
  • Not explicitly stated in the abstract.
  • The authors identify that "existing RAG and document analytics systems fail to achieve all query types simultaneously," indicating a gap in unified systems that can handle retrieval, knowledge discove
  • The authors identify "open challenges in efficiency, fine-grained representation, and robustness" as key areas requiring future progress in document AI and Multimodal RAG systems.

Representative papers

Related priority directions