3 papers
physics.soc-ph2026
Peer-Voted LLM-Agent Stress Tests Find Feed-Induced Lexical Convergence but No Reliable Matched-Exposure Advantage for Distributed Sources
Rana Muhammad Usman, Dominic Williamson
Population-level behavior in large-language-model (LLM) agents cannot be characterized by single-agent benchmarks. We introduce PV-SST, a peer-voted social-platform testbed, and re…
cs.LG2026
PhantomFill: When the Form Demands an Answer, Language Models Invent One
Rana Muhammad Usman
Language models in production do not write prose. They fill forms: JSON fields, function arguments, extraction templates. We show that the form itself causes hallucination. We ask…
cs.AI2026
Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults
Rana Muhammad Usman
LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queues, yet safety evaluations a…