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20232026
most citedGenerative Adversarial Networks for Data Augmentation

2 citations · 8 across the 23 of their papers we have counts for

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9 papers · 1 filter

cs.NI2026

Computing All-Pairs Shortest Communication Time Paths for Periodically Varying Satellite Networks

Koushik Sinha, Dibakar Saha, Sai Puppala +1

We address the problem of designing an efficient algorithm for computing the all-pairs shortest-time paths in time-varying networks, specifically targeting the dynamic topological…

cs.AI2026

FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study

Sai Puppala, Koushik Sinha, Bhabani P. Sinha

Satellite mega-constellations are emerging as large-scale sensing, communication, and computation fabrics, yet their learning architectures remain largely inherited from terrestria…

cs.CR2026

Influence Is Not Authority: When Causal Guardrail Signals Make Legitimate Tool Use Look Like an Attack in Tool-Using LLM Agents

Tanzim Ahad, Ismail Hossain, Md Jahangir Alam +3

The key limitation of current state-of-the-art influence-based guardrails is that they do not reliably distinguish a legitimate, user-authorized action from a malicious, unauthoriz…

cs.CR2026

SkillVetBench: LLM-as-Judge for Multi-Dimensional Security Risk Evaluation in Open-Source LLM Agent Skills

Ismail Hossain, Sai Puppala, Md Jahangir Alam +2

Open-source LLM agent ecosystems are growing rapidly, yet the security of community-contributed skills - modular tool definitions that extend agent capabilities - remains largely u…

cs.CR2026

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

Ismail Hossain, Sai Puppala, Zhuoran Lu +2

Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supply-chain risk: malicious contr…

cs.CR2026

The Misattribution Gap: When Memory Poisoning Looks Like Model Failure in Agentic AI Systems

Tanzim Ahad, Ismail Hossain, Md Jahangir Alam +3

Multi-agent AI pipelines typically assume that agent misconduct originates from model misalignment. We identify a structural failure in this assumption, the \emph{Misattribution Ga…

cs.CR2026

The Art of the Jailbreak: Formulating Jailbreak Attacks for LLM Security Beyond Binary Scoring

Ismail Hossain, Tanzim Ahad, Md Jahangir Alam +3

Jailbreak attacks -- adversarial prompts that bypass LLM alignment through purely linguistic manipulation -- pose a growing operational security threat, yet the field lacks large-s…

cs.CR2026

Semantic Intent Fragmentation: A Single-Shot Compositional Attack on Multi-Agent AI Pipelines

Tanzim Ahad, Ismail Hossain, Md Jahangir Alam +4

We introduce Semantic Intent Fragmentation (SIF), an attack class against LLM orchestration systems where a single, legitimately phrased request causes an orchestrator to decompose…

cs.CR2026

Agent-Fence: Mapping Security Vulnerabilities Across Deep Research Agents

Sai Puppala, Ismail Hossain, Md Jahangir Alam +5

Large language models are increasingly deployed as *deep agents* that plan, maintain persistent state, and invoke external tools, shifting safety failures from unsafe text to unsaf…