3 papers
cs.CL2026
Safety Measurements for Fine-tuned LLMs Should be Grounded in Capability
Krishnapriya Vishnubhotla, Hillary Dawkins, Isar Nejadgholi +1
Adapting foundation large language models to a user's task or preferred style through fine-tuning can result in compromising the model's safety. Previous works examined the effects…
cs.CL2026
LLM Judges Inconsistently Disagree Across Safety Criteria and Harm Categories
Krishnapriya Vishnubhotla, Sowmya Vajjala, Akriti Vij +1
We evaluate the consistency of automated judges in conducting a multi-dimensional safety evaluation in a reference-free setup. Our results indicate that Large Language Models are u…
cs.CL2026
Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory
Isar Nejadgholi, Masoud Kianpour, Krishnapriya Vishnubhotla +1
Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities considered in much of the liter…