Cognitive Linguistic Identity Fusion Score (CLIFS): A Scalable Cognition‐Informed Approach to Quantifying Identity Fusion from Text (2025.emnlp-main)
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| Challenge: | Existing methods for measuring identity fusion are limited and require controlled surveys or direct field contact. |
| Approach: | They propose a new metric that integrates cognitive linguistics with large language models to measure identity fusion. |
| Outcome: | The proposed metric outperforms existing methods and human annotations in violence risk assessment. |
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| Challenge: | Representative bias is a tendency of Large Language Models to generate outputs that mirror the experiences of certain identity groups, and affinity bias is an evaluative preference for specific narratives. |
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Fusion-Eval: Integrating Assistant Evaluators with LLMs (2024.emnlp-industry)
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| Challenge: | Recent studies have employed large language models (LLMs) as reference-free metrics for NLG evaluation, enhancing adaptability to new tasks tasks. |
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Value Portrait: Assessing Language Models’ Values through Psychometrically and Ecologically Valid Items (2025.acl-long)
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| Challenge: | Existing benchmarks rely on human annotations that are vulnerable to value-related biases. |
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LLMs for Generating and Evaluating Counterfactuals: A Comprehensive Study (2024.findings-emnlp)
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Generative Psycho-Lexical Approach for Constructing Value Systems in Large Language Models (2025.acl-long)
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| Challenge: | Large Language Models (LLMs) have raised concerns regarding their intrinsic values. |
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Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Value (2024.naacl-long)
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| Challenge: | Existing work specifies values as risk criteria formulated in the AI community, e.g., fairness and privacy protection, suffering from poor clarity, adaptability and transparency. |
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Systematic Evaluation of Auto-Encoding and Large Language Model Representations for Capturing Author States and Traits (2025.findings-acl)
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Khushboo Singh, Vasudha Varadarajan, Adithya V Ganesan, August Håkan Nilsson, Nikita Soni, Syeda Mahwish, Pranav Chitale, Ryan L. Boyd, Lyle Ungar, Richard N Rosenthal, H. Schwartz
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Measuring scalar constructs in social science with LLMs (2025.emnlp-main)
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Hauke Licht, Rupak Sarkar, Patrick Y. Wu, Pranav Goel, Niklas Stoehr, Elliott Ash, Alexander Miserlis Hoyle
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Measuring Psychological Depth in Language Models (2024.emnlp-main)
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Fabrice Harel-Canada, Hanyu Zhou, Sreya Muppalla, Zeynep Yildiz, Miryung Kim, Amit Sahai, Nanyun Peng
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CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation (2020.coling-demos)
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| Challenge: | Existing tools for evaluation of word embeddings are extrinsic and intrinsic methods, but they do not accurately reflect the meaning of words. |
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