Author

Sahil Wadhwa

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#machine learning Preprint Sep 2026

FinRT: Distilling Adaptive Red-Teaming Strategies into Reusable Adversarial Generators in Consumer Finance

In regulated industries like consumer finance, seemingly harmless user queries can exploit large language model vulnerabilities, triggering safety failures and pushing responses dangerously close to policy limits. Existing automated red-teaming methods trade off attack effectiveness against generation cost, while treat...

Rikhiya Ghosh, Himanshu Kumar, Sriram Venkatapathy et al. · 0 citations

Preprint Aug 2026

Beyond the Vacuum: Combinatorial Strategy Selection for Competitor-Aware Generative Engine Optimization

This work formalizes GEO as a competitor-aware strategy selection problem and proposes a two-phase pipeline to solve it, which achieves state-of-the-art performance across several impression metrics over existing agentic and single-heuristic methods on both geo-bench and the authors' synthetically augmented competitive...

Vaibhav Sourirajan, Yao Zhang, Himanshu Kumar et al. · 0 citations

Preprint Aug 2026

Workspace Topology as an Attack Vector in Agentic Coding Assistants

It is found that workspace topology measurably affects IPI success, and changes in codebase modularity can significantly alter the Attack Success Rate (ASR), with highly modular environments demonstrating significantly lower attack success rates.

A. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Validity-Aware Jailbreak Evaluation for Large Language Models

This work proposes Sequential Epistemic and Action-Level Validation (SEAV), a verification-centric jailbreak evaluation framework that decomposes responses into ordered steps and evaluates both validity and correctness, and shows that enforcing correctness substantially reshapes measured robustness.

Qilong Wu, Sahil Wadhwa, Pranab Mohanty et al. · 0 citations