Learning to Play Like Humans: A Framework for LLM Adaptation in Interactive Fiction Games (2025.findings-acl)
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| Challenge: | Existing approaches prioritize task-specific performance metrics over human-like comprehension of narrative context and gameplay logic. |
| Approach: | They propose a framework that guides Large Language Models to learn and play IF games systematically. |
| Outcome: | The proposed framework aligns LLMs-based agents’ behavior with narrative intent and commonsense constraints to deliver more interpretable, human-like performance. |
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| Challenge: | Interactive Fiction (IF) games with real human-written natural language texts provide a new natural evaluation for language understanding techniques. |
| Approach: | They propose to re-formulate IF game solving as Multi-Passage Reading Comprehension tasks using context-query attention mechanisms and structured prediction to efficiently generate and evaluate action outputs. |
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| Challenge: | Existing approaches to ground LLMs in textual interactions have been limited due to low computational efficiency and limited performance. |
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Zhiheng Xi, Yiwen Ding, Wenxiang Chen, Boyang Hong, Honglin Guo, Junzhe Wang, Xin Guo, Dingwen Yang, Chenyang Liao, Wei He, Songyang Gao, Lu Chen, Rui Zheng, Yicheng Zou, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang
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| Challenge: | In this study, we explore the application of Large Language Models (LLMs) in Jubensha, a Chinese detective role-playing game and a novel area in Artificial Intelligence (AI) driven gaming. |
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Kranti Chalamalasetti, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen
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HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing (2026.findings-acl)
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Chengyu Du, Xintao Wang, Aili Chen, Weiyuan Li, Rui Xu, Junteng Liu, Zishan Huang, Rong Tian, Zijun Sun, Yuhao Li, Liheng Feng, Deming Ding, Pengyu Zhao, Yanghua Xiao
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JECC: Commonsense Reasoning Tasks Derived from Interactive Fictions (2023.findings-acl)
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| Challenge: | Existing benchmarks focus on a single reasoning type and ask human annotators to write candidate statements related to the particular type of commonsense. |
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| Challenge: | Existing studies have focused on the role of immersion and agency in interactive drama. |
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NarrativePlay: Interactive Narrative Understanding (2024.eacl-demo)
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| Challenge: | Existing systems for interactive agents focus on specific capabilities in predetermined scenarios. |
| Approach: | They propose a novel system that allows users to role-play a fictional character and interact with other characters in narratives in an immersive environment. |
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Character-LLM: A Trainable Agent for Role-Playing (2023.emnlp-main)
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| Challenge: | Large language models (LLMs) can be used to simulate human behaviors . a recent study suggests that LLMs can be more effective at generating human behavior . |
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