3 citations · 5 across the 8 of their papers we have counts for
8 papers · 1 filter
LLM Harms: A Taxonomy and Discussion
Kevin Chen, Saleh Afroogh, Abhejay Murali +3
This study addresses categories of harm surrounding Large Language Models (LLMs) in the field of artificial intelligence. It addresses five categories of harms addressed before, du…
Evaluating LLM Safety Across Child Development Stages: A Simulated Agent Approach
Abhejay Murali, Saleh Afroogh, Kevin Chen +3
Current safety alignment for Large Language Models (LLMs) implicitly optimizes for a "modal adult user," leaving models vulnerable to distributional shifts in user cognition. We pr…
Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions
Junfeng Jiao, Saleh Afroogh, Kevin Chen +3
As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical impera…
LLM Ethics Benchmark: A Three-Dimensional Assessment System for Evaluating Moral Reasoning in Large Language Models
Junfeng Jiao, Saleh Afroogh, Abhejay Murali +3
This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical…
LLMs and Childhood Safety: Identifying Risks and Proposing a Protection Framework for Safe Child-LLM Interaction
Junfeng Jiao, Saleh Afroogh, Kevin Chen +3
Large Language Models (LLMs) are increasingly embedded in child-facing contexts such as education, companionship, creative tools, but their deployment raises safety, privacy, devel…
IGGA: A Dataset of Industrial Guidelines and Policy Statements for Generative AIs
Junfeng Jiao, Saleh Afroogh, Kevin Chen +2
This paper introduces IGGA, a dataset of 160 industry guidelines and policy statements for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in industry and workpla…