3 papers
cs.AI2026
PAANI : On Device Visual Evidence Fusion and Explainable Guidance for River Robot Simulation
Savio Cardoz, Santhiya Rajan
Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained platforms, converting imperfec…
cs.MA2026
Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines
Santhiya Rajan, Samuel Mugel, Roman Orus
Air-gapped and on-premises language-model agents can silently omit decision-critical facts at any boundary between source ingestion and final answer generation. We present a nine-l…
cs.AI2026
ProvenanceGuard: Source-Aware Factuality Verification for MCP-Based LLM Agents
Ander Alvarez, Santhiya Rajan, Alessandro Genuardi +3
Tool-using LLM agents increasingly use the Model Context Protocol (MCP) to answer from heterogeneous evidence sources, including search, APIs, databases, clinical records, and form…