TALES: Text Adventure Learning Environment Suite
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Abstract (arXiv)
Reasoning is an essential skill to enable Large Language Models (LLMs) to interact with the world. As tasks become more complex, they demand increasingly sophisticated and diverse reasoning capabilities for sequential decision-making, requiring structured reasoning over the context history to determine the next best action. We introduce TALES, a diverse collection of synthetic and human-written text-adventure games designed to challenge and evaluate diverse reasoning capabilities. We present results over a range of LLMs, open- and closed-weights, performing a qualitative analysis on the top performing models. Despite an impressive showing on synthetic games, even the top LLM-driven agents fail to achieve 15% on games designed for human enjoyment. Code and visualization of the experiments can be found at https://microsoft.github.io/tale-suite.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 35 of its 43 references that are in the map. First posted on arXiv 19 Apr 2025.
Builds on
35 of 43 references.
References · 35
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
- 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,205
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- 2024AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agentscited by 339
- 2018TextWorld: A Learning Environment for Text-based Gamescited by 310
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- 2023ADaPT: As-Needed Decomposition and Planning with Language Modelscited by 177
- 2019Interactive Fiction Games: A Colossal Adventurecited by 168
- 2023SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Taskscited by 168
- 2020Keep CALM and Explore: Language Models for Action Generation in Text-based Gamescited by 108
23 more
- 2020Graph Constrained Reinforcement Learning for Natural Language Action Spacescited by 80
- 2023Evaluating Cognitive Maps and Planning in Large Language Models with CogEvalcited by 77
- 2015Language Understanding for Text-based Games Using Deep Reinforcement Learningcited by 71
- 2024Agent Planning with World Knowledge Modelcited by 70
- 2018Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learningcited by 53
- 2020How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worldscited by 38
- 2018Counting to Explore and Generalize in Text-based Gamescited by 36
- 2024Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Modelscited by 33
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Built on by
Citing papers per year: 2025: 4; 2026: 7.
11 papers.
- 2026WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Gamescited by 12
- 2025PuzzleJAX: A Benchmark for Reasoning and Learningcited by 4
- 2025A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembenchcited by 3
- 2026Sample-Efficient Learning from Agent Experiencecited by 3
- 2025Dual-Scale World Models for LLM Agents Towards Hard-Exploration Problemscited by 2
- 2026Code Owns the Simulation, Jev Owns the Evaluationcited by 1
- 2025ByteSized32Refactored: Towards an Extensible Interactive Text Games Corpus for LLM World Modeling and Evaluationcited by 0
- 2026LACE: Lattice Attention for Cross-thread Explorationcited by 0
- 2026DORA Explorer: Improving the Exploration Ability of LLMs Without Trainingcited by 0
- 2026Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+cited by 0
- 2026Reading Right, Acting Wrong: Diagnosing Decision Failures of System One Models in Agent Loopscited by 0
- 2026Reading Right, Acting Wrong: Diagnosing Decision Failures of System One Models in Agent Loops13 Oct 2026
- 2026Code Owns the Simulation, Jev Owns the Evaluation1 Oct 2026
- 2026Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+2 Aug 2026
- 2026Sample-Efficient Learning from Agent Experience23 Jul 2026
- 2026WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games17 May 2026
- 2026DORA Explorer: Improving the Exploration Ability of LLMs Without Training19 Apr 2026
- 2026LACE: Lattice Attention for Cross-thread Exploration16 Apr 2026
- 2025Dual-Scale World Models for LLM Agents Towards Hard-Exploration Problems28 Sep 2025
- 2025ByteSized32Refactored: Towards an Extensible Interactive Text Games Corpus for LLM World Modeling and Evaluation28 Sep 2025
- 2025PuzzleJAX: A Benchmark for Reasoning and Learning22 Aug 2025
- 2025A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembench11 Jul 2025
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- 2021Modeling Worlds in Text
- 2025TextGames: Learning to Self-Play Text-Based Puzzle Games via Language Model Reasoning
- 2026Playing With AI: How Do State-Of-The-Art Large Language Models Perform in the 1977 Text-Based Adventure Game Zork?
- 2026Reasoning Capabilities of Large Language Models. Lessons Learned from General Game Playing
- 2024TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMs
- 2025Haunted House: A text-based game for comparing the flexibility of mental models in humans and LLMs
- 2025Large Language Models as Pok'emon Battle Agents: Strategic Play and Content Generation
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