RedOne 2.0: Rethinking Domain-Specific LLM Post-Training for Social Networking Services Introduction: Why Social Networking Services Need Specialized Large Language Models? Core Question This Section Aims to Answer: What unique challenges do general-purpose large language models face when deployed in social networking services? General-purpose LLMs frequently underperform in social networking environments due to rapidly evolving trends, diverse cultural contexts, and heterogeneous workloads. Social platforms contain constantly changing content: new memes emerge overnight, community norms shift daily, and users communicate in multiple languages across different cultural backgrounds. These factors cause general models to misinterpret community-specific rules, over-enforce or under-enforce policies, and experience …
gpt-oss-safeguard in Practice: How to Run a Zero-Shot, Explainable Safety Classifier You Can Update in Minutes What is the shortest path to deploying a policy-driven safety filter when you have no labelled data and zero retraining budget? Hand your plain-language policy to gpt-oss-safeguard at inference time; it returns a verdict plus a human-readable chain-of-thought you can audit, all without retraining. Why This Model Exists: Core Problem & Immediate Answer Question answered: “Why do we need yet another safety model when Moderation APIs already exist?” Because classical classifiers require thousands of hand-labelled examples and weeks of retraining whenever the policy changes. …
A Practical Guide to the Sensitive-Lexicon Chinese Sensitive-Word List “ After reading this guide you will know what a sensitive-word list is and why it matters how to plug Sensitive-lexicon into any project in under five minutes how to stay on the right side of the law and avoid false positives the fifteen most common questions developers ask, answered in plain language 1 Why a Sensitive-Word List Exists Every day, millions of messages, comments and posts are published online. Forums, chat rooms, games and apps need a quick way to spot words that break local rules or platform policies. A …