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MOOCCubeX Large-Scale MOOC Concept-Graph Resource (Yu et al., 2021)
MOOCCubeX is a large knowledge-centered repository for adaptive learning in Massive Open Online Courses (MOOCs), released by the Tsinghua University Knowledge Engineering Group. It comprises 4{,}216 courses, 230{,}263 videos, 358{,}265 exercises, 637{,}572 fine-grained concepts, and roughly million behavioral records over 3{,}330{,}294 students, drawn from the XuetangX MOOC platform. The repository is organized around a weakly supervised fine-grained concept graph mined from course materials, so heterogeneous resources (videos, exercises, student logs, external web content) can be linked through shared concepts. Per-domain subsets — including a computer-science curriculum — are released for downstream concept-graph, prerequisite-learning, and adaptive-learning research.
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Auditable Strict-Parity Evaluation of Prerequisite-Graph Retrieval for RAG under Leakage Controls
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Reference: What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning
Reference: R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning
Reference: ojs.aaai.org
Reference: Prerequisite Relation Learning for Concepts in MOOCs
Reference: Course Prerequisite Relation (MOOC prerequisite dataset release page)
Reference: MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs
Reference: QASC: A Dataset for Question Answering via Sentence Composition
Reference: QASC: A Dataset for Question Answering via Sentence Composition (arXiv preprint)
Reference: ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
Reference: ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
Reference: arxiv.org
Reference: arxiv.org
Reference: Introduction to Information Retrieval
Reference: Evaluation measures (information retrieval)
Reference: REPLUG: Retrieval-Augmented Black-Box Language Models
Reference: arxiv.org
Reference: HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Reference: HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering (arXiv preprint)
Reference: HotpotQA Official Dataset and Leaderboard
Reference: Dense Passage Retrieval for Open-Domain Question Answering
Reference: Dense Passage Retrieval for Open-Domain Question Answering (arXiv preprint)
LectureBank Dataset
MOOC-CS Prerequisite Benchmark
QASC Question Answering Benchmark
Late-Interaction Neural Retrieval
Recall@k Retrieval Metric
RePlug Retrieval-Augmented Black-Box Language Model
HotpotQA Multi-Hop QA Benchmark
Single-Vector Dense Passage Retrieval
Reference: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Reference: How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG
Reference: arxiv.org
Unbiased GraphRAG Evaluation Framework (Zeng et al., 2025)
Reference: RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
Reference: arxiv.org
RAG vs Graph-RAG Controlled Comparison (Han et al., 2025)
Reference: Controlled Retrieval-augmented Context Evaluation for Long-form RAG
Reference: Controlled Retrieval-augmented Context Evaluation for Long-form RAG (ACL Anthology)
CRUX Controlled RAG Context Evaluation (Ju et al., 2025)
Reference: Anytime Heuristic Search
Reference: The Anatomy of a Large-Scale Hypertextual Web Search Engine