208 citations · 227 across the 6 of their papers we have counts for
7 papers · 1 filter
Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models
Fei Wang, Ninareh Mehrabi, Palash Goyal +3
Data is a crucial element in large language model (LLM) alignment. Recent studies have explored using LLMs for efficient data collection. However, LLM-generated data often suffers…
Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models
Ninareh Mehrabi, Palash Goyal, Apurv Verma +7
Natural language often contains ambiguities that can lead to misinterpretation and miscommunication. While humans can handle ambiguities effectively by asking clarifying questions…
An Analysis of the Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation
Jwala Dhamala, Varun Kumar, Rahul Gupta +2
Several prior works have shown that language models (LMs) can generate text containing harmful social biases and stereotypes. While decoding algorithms play a central role in deter…
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations
Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang +4
Multiple metrics have been introduced to measure fairness in various natural language processing tasks. These metrics can be roughly categorized into two categories: 1) \emph{extri…
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal
Umang Gupta, Jwala Dhamala, Varun Kumar +7
Language models excel at generating coherent text, and model compression techniques such as knowledge distillation have enabled their use in resource-constrained settings. However,…
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification
Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala +2
Existing bias mitigation methods to reduce disparities in model outcomes across cohorts have focused on data augmentation, debiasing model embeddings, or adding fairness-based opti…