5 papers
Adaptive Instruction Composition for Automated LLM Red-Teaming
Jesse Zymet, Andy Luo, Swapnil Shinde +2
Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifying effective strategies through…
STELP: Secure Transpilation and Execution of LLM-Generated Programs
Swapnil Shinde, Sahil Wadhwa, Andy Luo +2
Rapid evolution of Large Language Models (LLMs) has achieved major advances in reasoning, planning, and function-calling capabilities. Multi-agentic collaborative frameworks using…
ART: Adaptive Reasoning Trees for Explainable Claim Verification
Sahil Wadhwa, Himanshu Kumar, Guanqun Yang +4
Large Language Models (LLMs) are powerful candidates for complex decision-making, leveraging vast encoded knowledge and remarkable zero-shot abilities. However, their adoption in h…
A Multi-Stage Workflow for the Review of Marketing Content with Reasoning Large Language Models
Alberto Purpura, Emily Chen, Swapnil Shinde
Reasoning Large Language Models (LLMs) have shown promising results when tasked with solving complex problems. In this paper, we propose and evaluate a multi-stage workflow that le…
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…