Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research
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Abstract (arXiv)
"This paper introduces a new task and a new dataset", "we improve the state of the art in X by Y" -- it is rare to find a current natural language processing paper (or AI paper more generally) that does not contain such statements. What is mostly left implicit, however, is the assumption that this necessarily constitutes progress, and what it constitutes progress towards. Here, we make more precise the normally impressionistically used notions of language task and language game and ask how a research programme built on these might make progress towards the goal of modelling general language competence.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Aug 2019.
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Citing papers per year: 2023: 3; 2024: 1; 2025: 2.
6 papers.
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- 2024Auxiliary task demands mask the capabilities of smaller language modelscited by 54
- 2023Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategycited by 12
- 2025A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembenchcited by 3
- 2025Playpen: An Environment for Exploring Learning Through Conversational Interactioncited by 2
- 2025A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembench11 Jul 2025
- 2025Playpen: An Environment for Exploring Learning Through Conversational Interaction11 Apr 2025
- 2024Auxiliary task demands mask the capabilities of smaller language models3 Apr 2024
- 2023Sociotechnical Safety Evaluation of Generative AI Systems18 Oct 2023
- 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?10 Oct 2023
- 2023Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategy14 Apr 2023