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RePlug Retrieval-Augmented Black-Box Language Model
RePlug is a retrieval-augmented language modeling framework introduced by Shi et al. (2023) that treats the language model as a frozen black box: the LM's parameters and architecture are never modified, and the only interface used is input-output. Given a query, a dense retriever fetches the top- documents from an external corpus, each retrieved document is independently prepended to the query, and the resulting per-document LM next-token distributions are combined via a retrieval-score-weighted ensemble. An optional extension, RePlug LSR (LM-Supervised Retrieval), tunes the retriever using the language model's own likelihood of the target output as a supervision signal, so the retriever learns to surface documents that actually improve LM predictions. Because the LM is untouched, RePlug can be paired with any off-the-shelf retriever (e.g. a late-interaction retriever such as ColBERTv2) and any black-box LM, which is why the combined ColBERTv2/RePlug system can appear as a strict-parity baseline in retrieval-augmented QA evaluations.
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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