2 papers
cs.CL2026
When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression
Riku Kisako, Hayato Tsukagoshi, Ryohei Sasano
Recent high-performing text embedding models often produce high-dimensional real-valued vectors, resulting in substantial storage and computational costs. To address this issue, em…
cs.CL2025
On Representational Dissociation of Language and Arithmetic in Large Language Models
Riku Kisako, Tatsuki Kuribayashi, Ryohei Sasano
The association between language and (non-linguistic) thinking ability in humans has long been debated, and recently, neuroscientific evidence of brain activity patterns has been c…