Retrieval-augmented generation
CompAct
CompAct: Compressing Retrieved Documents Actively for Question Answering
Superseded — cited as a baseline and beaten by newer methods
0 papers critique it · 5 beat it on benchmarks
Beaten on benchmarks
Head-to-head results where a newer method reports beating CompAct. Values are copied from the source paper's tables — verify against the cited paper.
OkraLong beats CompAct
51.4 vs 30.9
Ext2Gen-R2 beats CompAct
0.463 vs 0.343
Acc · [Llama3.1-8b-instruct backbone]
Aligning Extraction and Generation for Robust Retrieval-Augmented GenerationAttnComp beats CompAct
19.6 vs 16.5
QREAM-FT beats CompAct
45.6 vs 40.1
Accuracy · [Standard RAG Pipeline with Llama-3-8B-Instruct]
Align Documents to Questions: Question-Oriented Document Rewriting for Retrieval-Augmented GenerationOreo beats CompAct
0.658 vs 0.5974
F1 · [Multi-hop QA with Flan-T5]
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation
What to use instead
Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.
- Bottleneck Attention Intervention for Recovery (BAIR)The Cost of Context: Mitigating Textual Bias in Multimodal Retrieval-Augmented GenerationMay 7, 2026
- QREAMAlign Documents to Questions: Question-Oriented Document Rewriting for Retrieval-Augmented GenerationApr 19, 2026
- CoCR-RAGCoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context ReconstructionMar 25, 2026
- Jan 26, 2026
- Jan 19, 2026
- Sep 22, 2025
- Contextual Influence Value (CI value)Influence Guided Context Selection for Effective Retrieval-Augmented GenerationSep 21, 2025