Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning
October 14, 2025 ยท Declared Dead ยท ๐ 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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