7 papers
Temporal Multi-Signal Fusion for Token-Level Hallucination Detection
Igor Itkin
Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the generating model is confidently wrong. This paper instead treats…
Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop
Igor Itkin
Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase behaviour, stylised facts, a…
How Much Does Correctness Cost? Budgeted Placement of Strong Correctors in a Weak Multi-Agent Swarm
Igor Itkin
A cheap swarm of unreliable agents can be steered to a correct consensus by a few strong, expensive "oracle" correctors. We ask how much one must spend, and where to place the orac…
Quickest Detection of Hallucination Onset: Delay Bounds and Learned CUSUM Statistics
Igor Itkin
Token-level hallucination detectors are evaluated as classifiers, by AUC over all tokens, yet a streaming monitor is judged by its reaction time: the number of tokens that pass bet…
Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement
Igor Itkin
Multi-agent large language model (LLM) systems often rely on verifier and critic agents to suppress hallucinations, but verification is delayed. During this delay, false claims can…
Selective Control under Noisy Perception: Governance Failures Hidden by Aggregate Metrics in Modular Networks
Igor Itkin
A content-moderation system can score well on every standard accuracy metric and still cause real harm, if its mistakes fall on the few users who connect otherwise separate communi…