Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning

October 14, 2025 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Guangzhi Wang, Kai Li, Yinghao Jiao, Zhi Liu arXiv ID 2511.13726 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.IR Citations 0 Venue arXiv.org Last Checked 6 months ago
Abstract
We propose RT (Refine Thought), a method that can enhance the semantic rea-soning ability of text embedding models. The method obtains the final semanticrepresentation by running multiple forward passes of the text embedding model.Experiments show that RT achieves significant improvements on semantic reason-ing tasks in BRIGHT and the person job matching benchmark PJBenchmark1, while maintaining consistent performance on general-purpose semantic under-standing tasks such as C-MTEB. Our results indicate that RT is effective becauseit further activates the semantic reasoning ability learned during pretraining bydecoder-only text embedding models(e.g., Qwen3-Embedding-8B). RT canbe seen as a test-time inference method.
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