mlsanityData to 7 Oct 2026

Automated Crossword Solving

arXiv 2205.09665 ↗First posted 19 May 2022cs.CLcited by 9

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Abstract (arXiv)

We present the Berkeley Crossword Solver, a state-of-the-art approach for automatically solving crossword puzzles. Our system works by generating answer candidates for each crossword clue using neural question answering models and then combines loopy belief propagation with local search to find full puzzle solutions. Compared to existing approaches, our system improves exact puzzle accuracy from 71% to 82% on crosswords from The New York Times and obtains 99.9% letter accuracy on themeless puzzles. Additionally, in 2021, a hybrid of our system and the existing Dr.Fill system outperformed all human competitors for the first time at the American Crossword Puzzle Tournament. To facilitate research on question answering and crossword solving, we analyze our system's remaining errors and release a dataset of over six million question-answer pairs.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 17 of its 29 references that are in the map. First posted on arXiv 19 May 2022.

Builds on

17 of 29 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2017Billion-scale similarity search with GPUscited by 2,477
  4. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
  5. 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 713
  6. 2018Annotation Artifacts in Natural Language Inference Datacited by 656
  7. 2021ByT5: Towards a token-free future with pre-trained byte-to-byte modelscited by 504
  8. 2020AmbigQA: Answering Ambiguous Open-domain Questionscited by 385
  9. 2019On NMT Search Errors and Model Errors: Cat Got Your Tongue?cited by 114
  10. 2019Compositional Questions Do Not Necessitate Multi-hop Reasoningcited by 87
  11. 2019Calibration of Encoder Decoder Models for Neural Machine Translationcited by 67
  12. 2021Offline Model-Based Optimization via Normalized Maximum Likelihood Estimationcited by 38
5 more
  1. 2019Quizbowl: The Case for Incremental Question Answeringcited by 36
  2. 2015Learning to Understand Phrases by Embedding the Dictionarycited by 33
  3. 2021Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLPcited by 16
  4. 2021Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Languagecited by 15
  5. 2014Dr.Fill: Crosswords and an Implemented Solver for Singly Weighted CSPscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 2; 2025: 2; 2026: 1.

9 papers.