mlsanityData to 7 Oct 2026

MultiReQA: A Cross-Domain Evaluation for Retrieval Question Answering Models

arXiv 2005.02507 ↗First posted 5 May 2020cs.CL cs.LGcited by 23

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Abstract (arXiv)

Retrieval question answering (ReQA) is the task of retrieving a sentence-level answer to a question from an open corpus (Ahmad et al.,2019).This paper presents MultiReQA, anew multi-domain ReQA evaluation suite com-posed of eight retrieval QA tasks drawn from publicly available QA datasets. We provide the first systematic retrieval based evaluation over these datasets using two supervised neural models, based on fine-tuning BERT andUSE-QA models respectively, as well as a surprisingly strong information retrieval baseline,BM25. Five of these tasks contain both train-ing and test data, while three contain test data only. Performance on the five tasks with train-ing data shows that while a general model covering all domains is achievable, the best performance is often obtained by training exclusively on in-domain data.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 May 2020.

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Citing papers per year: 2021: 6; 2022: 4; 2023: 4; 2024: 4; 2025: 3; 2026: 2.

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  1. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  2. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  3. 2021TWEAC: Transformer with Extendable QA Agent Classifierscited by 37
  4. 2022Reasoning over Public and Private Data in Retrieval-Based Systemscited by 21
  5. 2022Exploring Dual Encoder Architectures for Question Answeringcited by 19
  6. 2025Collapse of Dense Retrievers: Short, Early, and Literal Biases Outranking Factual Evidencecited by 16
  7. 2021An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainabilitycited by 15
  8. 2023SamToNe: Improving Contrastive Loss for Dual Encoder Retrieval Models with Same Tower Negativescited by 9
  9. 2021A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Modelscited by 8
  10. 2022Learning to Reuse Distractors to support Multiple Choice Question Generation in Educationcited by 7
  11. 2023Policy-Gradient Training of Language Models for Rankingcited by 5
  12. 2024M2QA: Multi-domain Multilingual Question Answeringcited by 5
11 more
  1. 2024DEXTER: A Benchmark for open-domain Complex Question Answering using LLMscited by 4
  2. 2022Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challengescited by 3
  3. 2024Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuningcited by 2
  4. 2024Backtracing: Retrieving the Cause of the Querycited by 2
  5. 2025K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressorcited by 2
  6. 2021Zero-Shot Estimation of Base Models' Weights in Ensemble of Machine Reading Comprehension Systems for Robust Generalizationcited by 1
  7. 2023JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its Applicationscited by 1
  8. 2025Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generationcited by 1
  9. 2023Towards Consistency Filtering-Free Unsupervised Learning for Dense Retrievalcited by 0
  10. 2026Semantically Orthogonal Framework for Citation Classification: Disentangling Intent and Contentcited by 0
  11. 2026Retrieval Sensitivity to Identity Signals in Queriescited by 0