2 citations · 7 across the 19 of their papers we have counts for
8 papers · 1 filter
Towards Geo-Culturally Grounded LLM Generations
Piyawat Lertvittayakumjorn, David Kinney, Vinodkumar Prabhakaran +2
Generative large language models (LLMs) have demonstrated gaps in diverse cultural awareness across the globe. We investigate the effect of retrieval augmented generation and searc…
Risks of Cultural Erasure in Large Language Models
Rida Qadri, Aida M. Davani, Kevin Robinson +1
Large language models are increasingly being integrated into applications that shape the production and discovery of societal knowledge such as search, online education, and travel…
D3CODE: Disentangling Disagreements in Data across Cultures on Offensiveness Detection and Evaluation
Aida Mostafazadeh Davani, Mark Díaz, Dylan Baker +1
While human annotations play a crucial role in language technologies, annotator subjectivity has long been overlooked in data collection. Recent studies that have critically examin…
GeniL: A Multilingual Dataset on Generalizing Language
Aida Mostafazadeh Davani, Sagar Gubbi, Sunipa Dev +2
Generative language models are transforming our digital ecosystem, but they often inherit societal biases, for instance stereotypes associating certain attributes with specific ide…
Naive Bayes-based Context Extension for Large Language Models
Jianlin Su, Murtadha Ahmed, Wenbo +3
Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…
SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypes
Mukul Bhutani, Kevin Robinson, Vinodkumar Prabhakaran +2
While generative multilingual models are rapidly being deployed, their safety and fairness evaluations are largely limited to resources collected in English. This is especially pro…
A Taxonomy of Rater Disagreements: Surveying Challenges & Opportunities from the Perspective of Annotating Online Toxicity
Wenbo Zhang, Hangzhi Guo, Ian D Kivlichan +3
Toxicity is an increasingly common and severe issue in online spaces. Consequently, a rich line of machine learning research over the past decade has focused on computationally det…
GRASP: A Disagreement Analysis Framework to Assess Group Associations in Perspectives
Vinodkumar Prabhakaran, Christopher Homan, Lora Aroyo +6
Human annotation plays a core role in machine learning -- annotations for supervised models, safety guardrails for generative models, and human feedback for reinforcement learning,…