Reasoning Quality Matters: Combating Reasoning Collapse in LLM-based Embedding Learning
Large Language Models (LLMs) have recently shown strong potential for producing context-rich text embeddings for retrieval. Most existing methods either treat embedding learning as passive feature extraction or exploit LLM reasoning through instruction following for better embedding optimization. However, specializatio...