14 citations · 41 across the 23 of their papers we have counts for
6 papers · 1 filter
Where Rules End and Judges Begin: Measuring the Judgment Boundary in Multi-Agent Systems Security
Shaswata Mitra, Raj Patel, Subash Neupane +3
LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content. Current defenses for MAS are typically evaluated in isol…
Can LLMs Reason Over Long Horizons? An Empirical Evaluation of Context Strategies for Longitudinal Clinical Reasoning
Taye Akinrele, Noorbakhsh Amiri Golilarz, Subash Neupane +2
Longitudinal clinical reasoning requires large language models (LLMs) to identify and integrate relevant evidence distributed across extended patient histories. Although long-conte…
Evaluating the NIST Bugs Framework Against CWE as a Successor for Automated Vulnerability Classification
Md Nazmul Hoque, Shaswata Mitra, Subash Neupane +2
Vulnerability classification based on root cause weaknesses is essential for numerous cybersecurity activities, where the Common Weakness Enumeration (CWE) serves as a public repos…
Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering
Himanshu Tripathi, Subash Neupane, Shaswata Mitra +3
Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential in clinical question answer…
How Compliant is Sepsis Treatment? An Expert-Guided Neuro-symbolic Pipeline for Generating Clinical Compliance Insights
Himanshu Tripathi, Kaushik Roy, Subash Neupane +1
Verifying whether clinical care follows evidence-based protocols is a natural neuro-symbolic problem, yet the safety-critical setting defeats either paradigm alone. We present an e…
Find Before You Fine-Tune: A Diagnostic Study of Small LLMs for Cybersecurity QA
Shaswata Mitra, Subash Neupane, Trisha Chakraborty +4
Large Language Models (LLMs) are increasingly fine-tuned for critical-domain Question-Answering (QA), yet choosing which small model to adapt, before paying the cost of adaptation,…