activity
20232025
most citedThe Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations

37 citations · 45 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Knowledge Graph Analysis of Legal Understanding and Violations in LLMs

Abha Jha, Abel Salinas, Fred Morstatter

The rise of Large Language Models (LLMs) offers transformative potential for interpreting complex legal frameworks, such as Title 18 Section 175 of the US Code, which governs biolo…

cs.CL2024

Risk and Response in Large Language Models: Evaluating Key Threat Categories

Bahareh Harandizadeh, Abel Salinas, Fred Morstatter

This paper explores the pressing issue of risk assessment in Large Language Models (LLMs) as they become increasingly prevalent in various applications. Focusing on how reward mode…

cs.CL2024★ 5 cited

The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance

Abel Salinas, Fred Morstatter

Large Language Models (LLMs) are regularly being used to label data across many domains and for myriad tasks. By simply asking the LLM for an answer, or ``prompting,'' practitioner…

cs.CL2023★ 3 cited

"Im not Racist but...": Discovering Bias in the Internal Knowledge of Large Language Models

Abel Salinas, Louis Penafiel, Robert McCormack +1

Large language models (LLMs) have garnered significant attention for their remarkable performance in a continuously expanding set of natural language processing tasks. However, the…

cs.CL2023★ 37 cited

The Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations

Abel Salinas, Parth Vipul Shah, Yuzhong Huang +2

Large Language Models (LLMs) have seen widespread deployment in various real-world applications. Understanding these biases is crucial to comprehend the potential downstream conseq…