Triangulating LLM Progress through Benchmarks, Games, and Cognitive Tests
Not on the map. Why?
Abstract (arXiv)
We examine three evaluation paradigms: standard benchmarks (e.g., MMLU and BBH), interactive games (e.g., Signalling Games or Taboo), and cognitive tests (e.g., for working memory or theory of mind). First, we investigate which of the former two-benchmarks or games-is most effective at discriminating LLMs of varying quality. Then, inspired by human cognitive assessments, we compile a suite of targeted tests that measure cognitive abilities deemed essential for effective language use, and we investigate their correlation with model performance in benchmarks and games. Our analyses reveal that interactive games are superior to standard benchmarks in discriminating models. Causal and logical reasoning correlate with both static and interactive tests, while differences emerge regarding core executive functions and social/emotional skills, which correlate more with games. We advocate for the development of new interactive benchmarks and targeted cognitive tasks inspired by assessing human abilities but designed specifically for LLMs.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 22 of its 84 references that are in the map. First posted on arXiv 20 Feb 2025.
Builds on
22 of 84 references.
References · 22
- 2024The Llama 3 Herd of Modelscited by 14,192
- 2020Measuring Massive Multitask Language Understandingcited by 7,768
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2024Qwen2 Technical Reportcited by 2,076
- 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,767
- 2024MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmarkcited by 1,758
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,718
- 2023Reasoning with Language Model is Planning with World Modelcited by 846
- 2020Experience Grounds Languagecited by 241
- 2024Are We Done with MMLU?cited by 178
- 2024ProSA: Assessing and Understanding the Prompt Sensitivity of LLMscited by 145
- 2024NATURAL PLAN: Benchmarking LLMs on Natural Language Planningcited by 125
10 more
- 2023Are Emergent Abilities in Large Language Models just In-Context Learning?cited by 109
- 2023CLadder: Assessing Causal Reasoning in Language Modelscited by 102
- 2022A fine-grained comparison of pragmatic language understanding in humans and language modelscited by 69
- 2023Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agentscited by 52
- 2024SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMscited by 51
- 2024Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thoughtcited by 34
- 2024Holmes: A Benchmark to Assess the Linguistic Competence of Language Modelscited by 26
- 2024InterIntent: Investigating Social Intelligence of LLMs via Intention Understanding in an Interactive Game Contextcited by 25
- 2023Working Memory Capacity of ChatGPT: An Empirical Studycited by 23
- 2023What A Situated Language-Using Agent Must be Able to Do: A Top-Down Analysiscited by 8
Built on by
Citing papers per year: 2025: 5; 2026: 6.
11 papers.
- 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
- 2025Do You Get the Hint? Benchmarking LLMs on the Board Game Conceptcited by 2
- 2025AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychologycited by 1
- 2025Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changescited by 1
- 2026Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Timecited by 1
- 2026CogArena: A Multimethod Evaluation of Cognitive Ability Structure in Large Language Modelscited by 0
- 2026Benchmarking the Benchmarks: Testing the Predictive Validity of Commonsense Benchmarkscited by 0
- 2026Investigating Knowledge Transfer Across Interactive Dialogue Gamescited by 0
- 2026Assessing mentalization in humans and large language modelscited by 0
- 2026Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning Modelscited by 0
- 2026Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning Models1 Oct 2026
- 2026Assessing mentalization in humans and large language models26 Aug 2026
- 2026Investigating Knowledge Transfer Across Interactive Dialogue Games25 Aug 2026
- 2026Benchmarking the Benchmarks: Testing the Predictive Validity of Commonsense Benchmarks4 Aug 2026
- 2026CogArena: A Multimethod Evaluation of Cognitive Ability Structure in Large Language Models27 Jul 2026
- 2026Mastering PokeGym: Graph-Guided Multimodal Evolution at Test Time9 Apr 2026
- 2025Do You Get the Hint? Benchmarking LLMs on the Board Game Concept15 Oct 2025
- 2025Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes12 Aug 2025
- 2025A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembench11 Jul 2025
- 2025AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychology22 Jun 2025
- 2025Playpen: An Environment for Exploring Learning Through Conversational Interaction11 Apr 2025
Similar, not cited
Close in wording, no citation either way
- 2024GameArena: Evaluating LLM Reasoning through Live Computer Games
- 2024Lost in the Logic: An Evaluation of Large Language Models' Reasoning Capabilities on LSAT Logic Games
- 2025Strong Memory, Weak Control: An Empirical Study of Executive Functioning in LLMs
- 2025Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applications
- 2025InMind: Evaluating LLMs in Capturing and Applying Individual Human Reasoning Styles
- 2023LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles
- 2026UniCog: Uncovering Cognitive Abilities of LLMs through Latent Mind Space Analysis
- 2025LLMs Judge Themselves: A Game-Theoretic Framework for Human-Aligned Evaluation