Research map / Large language models
Retrieval and knowledge: research map
1,064 accepted papers on Retrieval and knowledge in Large language models, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 2 clusters and 8 approaches. The busiest year so far is 2026.
Within Large language models, its share shrank from 11.5% in 2023–24 to 9.6% in 2025–26 (228 → 658 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
Explore Retrieval and knowledge in the interactive map
Working on something in this topic? Describe your idea in scime atlas to see which approach it falls under, the closest papers by meaning and how crowded the spot has become.
Approaches and key papers
question · answering · editing · 709 papers
Approaches in this cluster:
- Knowledge graph reasoning with LLMs (174 papers)
Ground LLM reasoning in knowledge graphs through logic-aware and graph-constrained methods. - Knowledge editing in LLMs (170 papers)
Edit or update stored knowledge in language models via parameters and memory modules. - Knowledge-augmented question answering (134 papers)
Inject graph or specialized knowledge into LLM prompts and benchmark question answering. - Explanatory and multiple-choice QA benchmarks (152 papers)
Create datasets and analyses for causal, structured, and multiple-choice question answering. - Domain-specific QA datasets (79 papers)
Build question answering and text-to-SQL resources for medical and scientific domains.
Most cited and most cited since 2024:
- Wizard of Wikipedia: Knowledge-Powered Conversational Agents (ICLR 2019 · 623 citations)
- (Comet-) Atomic 2020: On Symbolic and Neural Commonsense Knowledge Graphs (AAAI 2021 · 293 citations)
- Knowledge Graph Prompting for Multi-Document Question Answering (AAAI 2024 · 155 citations)
- FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering (AAAI 2024 · 77 citations)
retrieval augmented · augmented generation · generation rag · 355 papers
Approaches in this cluster:
- Retrieval-augmented reasoning (130 papers)
Improve retrieval-augmented LMs with context compression, search-enhanced reasoning, and generative retrieval. - RAG robustness and evaluation (164 papers)
Benchmark, critique, and harden retrieval-augmented generation against noise and attacks. - Long-context and personalized retrieval (61 papers)
Combine retrieval with long-context handling, calibration, and personalization benchmarks.
Most cited and most cited since 2024:
- Benchmarking Large Language Models in Retrieval-Augmented Generation (AAAI 2024 · 384 citations)
- Retrieval Augmented Language Model Pre-Training (ICML 2020 · 208 citations)
- HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models (NeurIPS 2024 · 105 citations)
- Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models (AAAI 2024 · 81 citations)
Related topics in Large language models
- Reasoning and chain of thought (1,557)
- Instruction and fine-tuning (871)
- Agents, code and math (1,722)
- Alignment and preferences (665)
- AI and society (827)
- Language, safety and interpretability (2,928)