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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
- A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics, and Challenges2025 · 13 citations
- VAIV bio-discovery service using transformer model and retrieval augmented generationSeonho Kim · 2024 · 6 citations
- An Evidence-Grounded Research Assistant for Functional Genomics and Drug Target AssessmentKsenia Sokolova · 2025 · 2 citations
- What Should I Cite? A RAG Benchmark for Academic Citation PredictionLeqi Zheng · 2026 · 1 citations
- ReactionSeek: LLM-powered literature data mining and knowledge discovery in organic synthesisJiawei Li · 2026 · 1 citations
- Structured information extraction from scientific text with large language modelsJohn Dagdelen · 2024 · 585 citations
- BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio‐Inspired MaterialsRachel K. Luu · 2023 · 107 citations
- A Survey on Student Use of Generative AI Chatbots for Academic ResearchAmy Deschenes · 2024 · 40 citations