Chang Wang

Large language models (LLMs) have become an important semantic infrastructure for modern recommender systems. A prevailing paradigm integrates LLM-derived semantic embeddings with collaborative representations via representation alignment, implicitly assuming that the two views encode a shared la...

While Large Language Models (LLMs) possess remarkable generative capabilities, generating diversified and engaging ad headlines in industrial applications remains challenging. Conventional training paradigms often suffer from mode collapse, converging on dominant data patterns and yielding homoge...