| Challenge: | Research shows that stereotypical ideas are often reflected in language use. |
| Approach: | They propose to use microportraits to investigate stereotyping in the media to explore various dimensions of stereotypation. |
| Outcome: | The proposed system allows social scientists to explore various dimensions of stereotyping compared to more basic models such as word clouds. |
Similar Papers
Quantifying Stereotypes in Language (2024.eacl-long)
Copied to clipboard
| Challenge: | Existing studies define a sentence as stereotypical and anti-stereotypical, but they lack a fine-grained quantification of stereotypes. |
| Approach: | They quantify stereotypes in language by annotating a dataset to quantify stereotype of sentences. |
| Outcome: | The proposed models validate the findings of the current studies. |
StereoDetect: Detecting Stereotypes and Anti-stereotypes the Correct Way Using Social Psychological Underpinnings (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Stereotypes are known to have harmful effects, making their detection critical . current research focuses on detecting and evaluating stereotypical biases . |
| Approach: | They propose a five-tuple definition and provide precise terminologies disentangling stereotypes, antistereotypes, stereotypical bias, and general bias. |
| Outcome: | The proposed framework disentangles stereotypes, antistereotypes, stereotypical bias, and general bias. |
Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets (2021.acl-long)
Copied to clipboard
| Challenge: | Several recent efforts have focused on benchmark datasets consisting of pairs of contrastive sentences, which are often accompanied by metrics that aggregate an NLP system’s behavior on these pairs into measurements of harms. |
| Approach: | They apply a measurement modeling lens to inventory pitfalls that threaten benchmarks' validity as measurement models for stereotyping. |
| Outcome: | The proposed benchmarks lack clarity and assumptions that affect how they conceptualize and operationalize stereotyping. |
StereoMap: Quantifying the Awareness of Human-like Stereotypes in Large Language Models (2023.emnlp-main)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have been observed to encode harmful associations present in the training data. |
| Approach: | They propose a framework to map LLMs' perceptions of how demographic groups have been viewed by society using the dimensions of Warmth and Competence. |
| Outcome: | The proposed framework maps LLMs’ perceptions of social groups using the dimensions of Warmth and Competence. |
Your Stereotypical Mileage May Vary: Practical Challenges of Evaluating Biases in Multiple Languages and Cultural Contexts (2024.lrec-main)
Copied to clipboard
Karen Fort, Laura Alonso Alemany, Luciana Benotti, Julien Bezançon, Claudia Borg, Marthese Borg, Yongjian Chen, Fanny Ducel, Yoann Dupont, Guido Ivetta, Zhijian Li, Margot Mieskes, Marco Naguib, Yuyan Qian, Matteo Radaelli, Wolfgang S. Schmeisser-Nieto, Emma Raimundo Schulz, Thiziri Saci, Sarah Saidi, Javier Torroba Marchante, Shilin Xie, Sergio E. Zanotto, Aurélie Névéol
| Challenge: | Recent studies have identified a gap in the availability of tools and resources to study bias in languages other than English and social contexts outside the north of America. |
| Approach: | They use stereotypes to build a corpus of sentence pairs that cover biases in seven cultural contexts. |
| Outcome: | The proposed resource covers a wide range of languages and cultural settings . it favors sentences that express stereotypes in most bias categories . |
Intersectional Stereotypes in Large Language Models: Dataset and Analysis (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies on intersectional stereotypes focus on broader, individual categories . current studies focus on single-group stereotypes, such as racial bias against African Americans . |
| Approach: | They propose to use a dataset of intersectional stereotypes curated with the ChatGPT model to analyze propagation in three contemporary LLMs. |
| Outcome: | The proposed dataset enables analysis of stereotype propagation in three contemporary LLMs. |
The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Text-to-image models are appealing for customizing visual ads and targeting specific populations. |
| Approach: | We examine the disparate level of persuasiveness of ads that are identical except for gender/race of the people portrayed. |
| Outcome: | The proposed technique is based on a demographic bias analysis of ads for different topics and a disparate level of persuasiveness of ads that are identical except for gender/race of the people portrayed. |
Social Bias Probing: Fairness Benchmarking for Language Models (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for evaluating social biases in language models have been limited to binary association tests on small datasets. |
| Approach: | They propose a framework for probing language models for social biases by assessing disparate treatment . they use a large-scale benchmark to examine the diversity of identities and stereotypes . |
| Outcome: | The proposed framework expands the analysis beyond the binary comparison of stereotypical versus anti-stereotypical identities to include a diverse range of identities and stereotypes. |
Rethinking Research on Stereotypes: An Analysis through Social Psychological and Computational Perspectives (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing research on stereotypical biases ignores literature on them and results in resource wastage. |
| Approach: | They argue that stereotypes are social constructs shaping human perception and behavior that can produce harmful outcomes under specific conditions. |
| Outcome: | The proposed models can inherit and amplify stereotypes under certain conditions. |
Theory-Grounded Measurement of U.S. Social Stereotypes in English Language Models (2022.naacl-main)
Copied to clipboard
| Challenge: | Pre-trained language models encode correlations between social groups and traits, like associating the group with the group. |
| Approach: | They adapt the Agency-Belief-Communion (ABC) stereotype model to a language model and introduce the sensitivity test (SeT) to measure stereotypical associations. |
| Outcome: | The proposed framework is used to measure stereotyping of intersectional identities in language models. |