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Geometric Latent Reasoning (GLR) introduces a geometric path-approximation method for latent reasoning in LLMs, enabling shorter generations while maintaining accuracy across mathematical reasoning benchmarks.
The paper introduces PASA, a robust watermarking algorithm for LLM-generated text that operates at the semantic level using latent embedding spaces to resist semantic-invariant attacks like paraphrasing.
Researchers introduce CSR-L and CS-MTEB benchmarks showing that code-switching queries degrade IR system performance by up to 27%, revealing embedding-space divergence that current multilingual techniques cannot fix.