Fixed 16-bit binary token codes can replace trainable input embeddings in 32-layer decoder-only models while maintaining comparable held-out perplexity on 17B tokens.
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Frozen Mamba patch-boundary readouts do not outperform mean pooling for sentence representations on SST-2, CoLA, MRPC, STS-B, and IMDb due to anisotropy (cosine similarity ~0.9999) and representational collapse (MCC=0 on CoLA).
citing papers explorer
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Language Models Without a Trainable Input Embedding Table: Learning from Fixed Minimal Binary Token Codes
Fixed 16-bit binary token codes can replace trainable input embeddings in 32-layer decoder-only models while maintaining comparable held-out perplexity on 17B tokens.
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Lost in State Space: Probing Frozen Mamba Representations
Frozen Mamba patch-boundary readouts do not outperform mean pooling for sentence representations on SST-2, CoLA, MRPC, STS-B, and IMDb due to anisotropy (cosine similarity ~0.9999) and representational collapse (MCC=0 on CoLA).