BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles
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Abstract (arXiv)
A riddle is a question or statement with double or veiled meanings, followed by an unexpected answer. Solving riddle is a challenging task for both machine and human, testing the capability of understanding figurative, creative natural language and reasoning with commonsense knowledge. We introduce BiRdQA, a bilingual multiple-choice question answering dataset with 6614 English riddles and 8751 Chinese riddles. For each riddle-answer pair, we provide four distractors with additional information from Wikipedia. The distractors are automatically generated at scale with minimal bias. Existing monolingual and multilingual QA models fail to perform well on our dataset, indicating that there is a long way to go before machine can beat human on solving tricky riddles. The dataset has been released to the community.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 37 of its 59 references that are in the map. First posted on arXiv 23 Sep 2021.
Builds on
37 of 59 references.
References · 37
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
- 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
- 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,793
- 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 913
- 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
- 2018Annotation Artifacts in Natural Language Inference Datacited by 656
- 2017Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problemscited by 642
25 more
- 2019On the Cross-lingual Transferability of Monolingual Representationscited by 575
- 2018From Recognition to Cognition: Visual Commonsense Reasoningcited by 553
- 2019ERNIE: Enhanced Language Representation with Informative Entitiescited by 525
- 2020UnifiedQA: Crossing Format Boundaries With a Single QA Systemcited by 475
- 2021QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answeringcited by 386
- 2019MLQA: Evaluating Cross-lingual Extractive Question Answeringcited by 339
- 2016NewsQA: A Machine Comprehension Datasetcited by 330
- 2019ERNIE: Enhanced Representation through Knowledge Integrationcited by 301
- 2018Hypothesis Only Baselines in Natural Language Inferencecited by 291
- 2019Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoningcited by 281
- 2016Bidirectional Attention Flow for Machine Comprehensioncited by 278
- 2020Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learningcited by 216
- 2020An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Modelscited by 133
- 2019Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answeringcited by 68
- 2021RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledgecited by 60
- 2021Zero-shot Fact Verification by Claim Generationcited by 42
- 2019What does BERT Learn from Multiple-Choice Reading Comprehension Datasets?cited by 30
- 2021DAGN: Discourse-Aware Graph Network for Logical Reasoningcited by 28
- 2020Automatic Distractor Generation for Multiple Choice Questions in Standard Testscited by 26
- 2018Generating Distractors for Reading Comprehension Questions from Real Examinationscited by 24
- 2021Measuring and Improving BERT's Mathematical Abilities by Predicting the Order of Reasoningcited by 23
- 2020RikiNet: Reading Wikipedia Pages for Natural Question Answeringcited by 21
- 2015sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddingscited by 20
- 2019BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novelscited by 17
- 2020Counterfactual Variable Control for Robust and Interpretable Question Answeringcited by 4
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Citing papers per year: 2022: 1; 2023: 1; 2024: 3; 2025: 3; 2026: 2.
10 papers.
- 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,033
- 2024Puzzle Solving using Reasoning of Large Language Models: A Surveycited by 44
- 2025A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Modelscited by 10
- 2023Long-Tailed Question Answering in an Open Worldcited by 7
- 2022CC-Riddle: A Question Answering Dataset of Chinese Character Riddlescited by 6
- 2024RISCORE: Enhancing In-Context Riddle Solving in Language Models through Context-Reconstructed Example Augmentationcited by 3
- 2025Adaptive Originality Filtering: Rejection Based Prompting and RiddleScore for Culturally Grounded Multilingual Riddle Generationcited by 1
- 2025BengaliFig: A Low-Resource Challenge for Figurative and Culturally Grounded Reasoning in Bengalicited by 1
- 2026RespondeoQA: a Benchmark for Bilingual Latin-English Question Answeringcited by 0
- 2026NSMQ Riddles: A Benchmark of Scientific and Mathematical Riddles for Quizzing Large Language Modelscited by 0
- 2026NSMQ Riddles: A Benchmark of Scientific and Mathematical Riddles for Quizzing Large Language Models8 May 2026
- 2026RespondeoQA: a Benchmark for Bilingual Latin-English Question Answering22 Apr 2026
- 2025BengaliFig: A Low-Resource Challenge for Figurative and Culturally Grounded Reasoning in Bengali25 Nov 2025
- 2025Adaptive Originality Filtering: Rejection Based Prompting and RiddleScore for Culturally Grounded Multilingual Riddle Generation26 Aug 2025
- 2025A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Models25 Jan 2025
- 2024RISCORE: Enhancing In-Context Riddle Solving in Language Models through Context-Reconstructed Example Augmentation24 Sep 2024
- 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites25 Apr 2024
- 2024Puzzle Solving using Reasoning of Large Language Models: A Survey17 Feb 2024
- 2023Long-Tailed Question Answering in an Open World11 May 2023
- 2022CC-Riddle: A Question Answering Dataset of Chinese Character Riddles28 Jun 2022