Introduction Running a Telegram community means constantly battling unwanted content: promotional links, phishing attempts, repeated nonsense, and language‑specific abuse. The classic defense—keyword filters—relies on a static list of banned words or patterns. While easy to set up, keyword filters become brittle quickly, generate false positives, and are easy for spammers to evade with minor text variations. Semantic anti‑spam, powered by large language models (LLMs), evaluates the meani...