46 citations · 50 across the 12 of their papers we have counts for
7 papers · 1 filter
FinRT: Distilling Adaptive Red-Teaming Strategies into Reusable Adversarial Generators in Consumer Finance
Rikhiya Ghosh, Himanshu Kumar, Sriram Venkatapathy +3
In regulated industries like consumer finance, seemingly harmless user queries can exploit large language model vulnerabilities, triggering safety failures and pushing responses da…
Validity-Aware Jailbreak Evaluation for Large Language Models
Qilong Wu, Sahil Wadhwa, Pranab Mohanty +2
Jailbreak robustness has become central to large language model (LLM) safety evaluation, yet prevailing methodologies rely primarily on refusal behavior, semantic resemblance, and…
Beyond the Vacuum: Combinatorial Strategy Selection for Competitor-Aware Generative Engine Optimization
Vaibhav Sourirajan, Yao Zhang, Himanshu Kumar +3
Generative Engine Optimization (GEO) has emerged as a novel paradigm for transforming content to increase visibility in Large Language Model (LLM) responses. Traditional GEO method…
Workspace Topology as an Attack Vector in Agentic Coding Assistants
Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9
Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…
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…