Reversing The Twenty Questions Game
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Abstract (arXiv)
Twenty questions is a widely popular verbal game. In recent years, many computerized versions of this game have been developed in which a user thinks of an entity and a computer attempts to guess this entity by asking a series of boolean-type (yes/no) questions. In this research, we aim to reverse this game by making the computer choose an entity at random. The human aims to guess this entity by quizzing the computer with natural language queries which the computer will then attempt to parse using a boolean question answering model. The game ends when the human is successfully able to guess the entity of the computer's choice.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 24 references that are in the map. First posted on arXiv 19 Jan 2023.
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10 of 24 references.
References · 10
- 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
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
- 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
- 2019BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questionscited by 2,140
- 2015A large annotated corpus for learning natural language inferencecited by 1,837
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,718
- 2019Resolving Gendered Ambiguous Pronouns with BERTcited by 16
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