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Melissa Kazemi Rad

Capital One, Rutgers University

4 papers hereh-index 557 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.LG1
affiliations
  • Capital One, Rutgers University

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2025

DynaGuard: A Dynamic Guardian Model With User-Defined Policies

Monte Hoover, Vatsal Baherwani, Neel Jain +7

Guardian models play a crucial role in ensuring the safety and ethical behavior of user-facing AI applications by enforcing guardrails and detecting harmful content. While standard…

cs.CL2025

GRAID: Synthetic Data Generation with Geometric Constraints and Multi-Agentic Reflection for Harmful Content Detection

Melissa Kazemi Rad, Alberto Purpura, Himanshu Kumar +2

We address the problem of data scarcity in harmful text classification for guardrailing applications and introduce GRAID (Geometric and Reflective AI-Driven Data Augmentation), a n…

cs.CL2025

Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models

Alberto Purpura, Sahil Wadhwa, Jesse Zymet +5

The rapid growth of Large Language Models (LLMs) presents significant privacy, security, and ethical concerns. While much research has proposed methods for defending LLM systems ag…

cs.CL2025

Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Melissa Kazemi Rad, Huy Nghiem, Andy Luo +3

Large Language Models (LLMs) have demonstrated powerful capabilities that render them valuable in different applications, including conversational AI products. It is paramount to e…

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