collaborators

7 papers

cs.SE2026

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…

cs.AI2026

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…

cs.LG2026

How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge

Junhong Lin, Bing Zhang, Song Wang +4

Large language models (LLMs) continue to struggle with knowledge-intensive questions that require up-to-date information and multi-hop reasoning. Augmenting LLMs with hybrid extern…

cs.AI2025

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…

cs.CR2025

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…

cs.LG2025

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…