AI RESEARCH
TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications
arXiv CS.LG
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ArXi:2604.17778v1 Announce Type: new Large language models (LLMs) are increasingly deployed in the telecommunications domain for critical tasks, relying heavily on Retrieval-Augmented Generation (RAG) to adapt general-purpose models to continuously evolving standards. However, a significant gap exists in evaluating the embedding models that power these RAG pipelines, as general-purpose benchmarks fail to capture the dense, acronym-heavy, and highly cross-referential nature of telecommunications corpora. To address this, we