/authors/arno-simons/Arno SimonsHugo Blox Builder (https://hugoblox.com)en-usWed, 01 Jul 2026 00:00:00 +0000/media/icon_hu33ac2647be7de12c09d025d9374b4e08_2029_512x512_fill_lanczos_center_3.png/authors/arno-simons//publication/rag4reports2026_pipeline/Wed, 01 Jul 2026 00:00:00 +0000/publication/rag4reports2026_pipeline/<p>Automating systematic reviews (SRs), i.e., evidence-driven analyses under explicit protocol constraints, is a natural target for retrieval-augmented generation and deep research agents, yet existing benchmarks evaluate isolated subtasks or assume fixed evidence inputs. We introduce RAG4SR-CS-200, a benchmark of 200 computer science systematic reviews designed for protocol-driven systematic review automation. Each instance comprises review objectives, research questions, eligibility criteria, cleaned full-text review structure, references, and extracted tables. These elements support evaluation across key tasks in systematic review creation such as literature retrieval, eligibility screening, citation-grounded review generation, and structured table generation, in both stage-wise and end-to-end settings. RAG4SR-CS-200 provides a foundation for developing more reliable and diagnosable deep research agents for scientific evidence synthesis. Code and data are publicly available.</p>