36 citations · 38 across the 6 of their papers we have counts for
8 papers · 1 filter
Robust Persona-Aware Toxicity Detection with Prompt Optimization and Learned Ensembling
Berk Atil, Rebecca J. Passonneau, Ninareh Mehrabi
Toxicity detection is inherently subjective, shaped by the diverse perspectives and social priors of different demographic groups. While ``pluralistic'' modeling as used in economi…
Do Methods to Jailbreak and Defend LLMs Generalize Across Languages?
Berk Atil, Rebecca J. Passonneau, Fred Morstatter
Large language models (LLMs) undergo safety alignment after training and tuning, yet recent work shows that safety can be bypassed through jailbreak attacks. While many jailbreaks…
Something Just Like TRuST : Toxicity Recognition of Span and Target
Berk Atil, Namrata Sureddy, Rebecca J. Passonneau
Toxic language includes content that is offensive, abusive, or that promotes harm. Progress in preventing toxic output from large language models (LLMs) is hampered by inconsistent…
Can LLMs Rank the Harmfulness of Smaller LLMs? We are Not There Yet
Berk Atil, Vipul Gupta, Sarkar Snigdha Sarathi Das +1
Large language models (LLMs) have become ubiquitous, thus it is important to understand their risks and limitations. Smaller LLMs can be deployed where compute resources are constr…
Joint Training for Selective Prediction
Zhaohui Li, Rebecca J. Passonneau
Classifier models are prevalent in natural language processing (NLP), often with high accuracy. Yet in real world settings, human-in-the-loop systems can foster trust in model outp…
Improving Model Evaluation using SMART Filtering of Benchmark Datasets
Vipul Gupta, Candace Ross, David Pantoja +3
One of the most challenging problems facing NLP today is evaluation. Some of the most pressing issues pertain to benchmark saturation, data contamination, and diversity in the qual…