Papers by Ziang Xiao
ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games (2023.emnlp-main)
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| Challenge: | We show that language models can generate explicit, interpretable, and interactive world models of scientific and common-sense reasoning tasks. |
| Approach: | They propose a corpus of 32 reasoning-focused text games expressed as hundreds of lines of Python code to facilitate this task. |
| Outcome: | The proposed games can generate runnable games on unseen topics in 28% of cases. |
Evaluating Evaluation Metrics: A Framework for Analyzing NLG Evaluation Metrics using Measurement Theory (2023.emnlp-main)
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| Challenge: | Existing evaluation metrics are conflated and can mislead models, resulting in downstream harms. |
| Approach: | They propose a framework for conceptualizing and evaluating the reliability and validity of evaluation metrics based on empirical data. |
| Outcome: | The proposed framework formalizes the source of measurement error and offers statistical tools for evaluating evaluation metrics based on empirical data. |
InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews (2024.acl-long)
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Xintao Wang, Yunze Xiao, Jen-tse Huang, Siyu Yuan, Rui Xu, Haoran Guo, Quan Tu, Yaying Fei, Ziang Leng, Wei Wang, Jiangjie Chen, Cheng Li, Yanghua Xiao
| Challenge: | Existing methods focus on knowledge and linguistic patterns of characters. |
| Approach: | They propose to evaluate character fidelity of role-playing agents with psychological scales . they propose to use psychological scale to measure personality traits of RPAs based on personality traits. |
| Outcome: | The proposed model reproduces character fidelity with psychological scales and shows that it is effective in measuring personality traits. |
Faux Polyglot: A Study on Information Disparity in Multilingual Large Language Models (2025.naacl-long)
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| Challenge: | Recent surge in multilingual large language models (LLMs) and Retrieval Augmented Generation (RAG) has significantly expanded conversational search across varied linguistic and cultural demographics. |
| Approach: | They found that LLMs displayed systemic bias towards information in the same language as query language in document retrieval and answer generation. |
| Outcome: | The results highlight the linguistic divide within multilingual LLMs in information search systems. |
Human-Centered Evaluation of Language Technologies (2024.emnlp-tutorials)
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| Challenge: | a lack of human-centered considerations about people’s needs for language technologies is causing an “evaluation crisis” in NLP. |
| Approach: | This tutorial introduces perspectives and methodologies from human-computer interaction (HCI) it will introduce what to evaluate for, how generalizable the results are to the real-world contexts, and pragmatic costs to conduct the evaluation. |
| Outcome: | This tutorial introduces perspectives and methodologies from human-computer interaction (HCI) the tutorial will also encourage reflection on how these HCI perspectives and methods can complement NLP evaluation through Q&A discussions and a hands-on exercise. |
Can Language Models Serve as Text-Based World Simulators? (2024.acl-short)
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| Challenge: | Recent advances in large language models (LLMs) have pointed towards an alternative approach by leveraging the huge amount of knowledge contained in their pre-training datasets. |
| Approach: | They build and use a benchmark to quantify how well text-based simulators can serve as text-driven world simulators. |
| Outcome: | The proposed benchmark aims to quantify how well language models can serve as world simulators. |
Generative Personality Simulation via Theory-Informed Structured Interview (2026.eacl-long)
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Pengda Wang, Huiqi Zou, Han Jiang, Hanjie Chen, Tianjun Sun, Xiaoyuan Yi, Ziang Xiao, Frederick L. Oswald
| Challenge: | Personality structured interviews are often lacking in advancing social science research. |
| Approach: | They propose a method to incorporate psychological insights into LLM simulations . they use a measure theory grounded evaluation procedure to evaluate reliability and validity . |
| Outcome: | The proposed method improves human-like heterogeneity in LLM-simulated personality data and predicts personality-related behavioral outcomes. |