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A Training-Free, Alignment-Free Approach to Corporate Intelligence: Application to SEC Filings
High-dimensional dense text embeddings and large language models face real obstacles in financial-disclosure analysis: context-window limits, hallucination risk, high computational cost, and the arbitrary rotation of vector spaces across independently trained models. We present a training-free, alig
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