7 papers
Runtime-Structured Task Decomposition for Agentic Coding Systems
Shubhi Asthana, Bing Zhang, Chad DeLuca +2
Agentic coding systems increasingly use large language models (LLMs) for software engineering tasks such as debugging, root cause analysis, and code review. However, many existing…
A Systematic Approach for Large Language Models Debugging
Basel Shbita, Anna Lisa Gentile, Bing Zhang +10
Large language models (LLMs) have become central to modern AI workflows, powering applications from open-ended text generation to complex agent-based reasoning. However, debugging…
STRIDE: A Systematic Framework for Selecting AI Modalities -- Agentic AI, AI Assistants, or LLM Calls
Shubhi Asthana, Bing Zhang, Chad DeLuca +2
The rapid shift from stateless large language models (LLMs) to autonomous, goal-driven agents raises a central question: When is agentic AI truly necessary? While agents enable mul…
OneShield -- the Next Generation of LLM Guardrails
Chad DeLuca, Anna Lisa Gentile, Shubhi Asthana +7
The rise of Large Language Models has created a general excitement about the great potential for a myriad of applications. While LLMs offer many possibilities, questions about safe…
Adaptive PII Mitigation Framework for Large Language Models
Shubhi Asthana, Ruchi Mahindru, Bing Zhang +1
Artificial Intelligence (AI) faces growing challenges from evolving data protection laws and enforcement practices worldwide. Regulations like GDPR and CCPA impose strict complianc…
Deploying Privacy Guardrails for LLMs: A Comparative Analysis of Real-World Applications
Shubhi Asthana, Bing Zhang, Ruchi Mahindru +3
The adoption of Large Language Models (LLMs) has revolutionized AI applications but poses significant challenges in safeguarding user privacy. Ensuring compliance with privacy regu…