# Retrieval-Augmented Generation: Research Digest

> 10 foundational papers with 46,470 combined citations, plus the latest arXiv preprints.

- **Canonical:** https://agentflare.org/scholar/retrieval-augmented-generation-research-digest.html
- **Updated:** 2026-10-18
- **Category:** scholar
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## Key data

- **Field:** retrieval augmented generation
- **Foundational:** 10
- **Recent (arXiv):** 8
- **Updated:** 2026-10-18

10 foundational papers with 46,470 combined citations, plus the latest arXiv preprints.

_…full analysis and the complete dataset are available to agents for $0.02 — fetch `/scholar/retrieval-augmented-generation-research-digest.data.json` (HTTP 402)._

## Sources

1. [Retrieval-augmented generation for knowledge-intensive nlp tasks](https://proceedings.neurips.cc/paper_files/paper/2020/hash/6b493230-Abstract.html)
2. [Searching for best practices in retrieval-augmented generation](https://aclanthology.org/2024.emnlp-main.981/)
3. [Retrieval-augmented generation for large language models: A survey](https://arxiv.org/abs/2312.10997)
4. [Evaluation of retrieval-augmented generation: A survey](https://link.springer.com/chapter/10.1007/978-981-96-1024-2_8)
5. [LightRAG: Simple and Fast Retrieval-Augmented Generation.](https://aclanthology.org/anthology-files/anthology-files/pdf/findings/2025.findings-emnlp.568.pdf)
6. [Active retrieval augmented generation](https://aclanthology.org/2023.emnlp-main.495/)
7. [Retrieval-augmented generation for natural language processing: A survey](https://link.springer.com/article/10.1007/s10462-026-11605-7)
8. [Retrieval-augmented generation for ai-generated content: A survey](https://link.springer.com/article/10.1007/s41019-025-00335-5)
9. [Graph retrieval-augmented generation: A survey](https://dl.acm.org/doi/abs/10.1145/3777378)
10. [Parametric retrieval augmented generation](https://dl.acm.org/doi/abs/10.1145/3726302.3729957)
11. [Private Retrieval Augmented Generation via Random Projection](https://arxiv.org/abs/2610.22297v1)
12. [Multi-sourced AI Tutor for Non-Native English Speaker Students](https://arxiv.org/abs/2610.22163v1)
13. [CARA: Causally Guided Retrieval Agent for Question Answering](https://arxiv.org/abs/2610.22017v1)
14. [TEM: Temporal State Tracking Memory for Large Language Model Agents](https://arxiv.org/abs/2610.21900v1)
15. [Loud and Clear: Making Visual Evidence Count in Multimodal Document RAG](https://arxiv.org/abs/2610.21318v1)
16. [Beyond Retrieval Failure: Understanding Why LLMs Miss Evidence in Multi-Hop RAG](https://arxiv.org/abs/2610.21184v1)
17. [Analyzing performance of Retrieval Augmented Generation models for Question Answering Tasks](https://arxiv.org/abs/2610.20419v2)
18. [GraphRAG-LTM: A Layered Threat Modeling Framework for Attacks on Graph Retrieval-Augmented Generation](https://arxiv.org/abs/2610.19549v1)

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