TIDE: Every Layer Knows the Token Beneath the Context
We revisit a universally accepted but under-examined design choice in every modern LLM: a token index is looked up once at the input embedding layer and then permanently discarded. This single-injection assumption induces two structural failures: (i) the Rare Token Problem, where a Zipf-type distribution of vocabulary causes rare-token embeddings are chronically under-trained due to receiving a fraction of the cumulative gradient signal compared to common tokens; and (ii) the Contextual Collapse Problem, where limited parameters models map distributionally similar tokens to indistinguishable hidden states. As an attempt to address both, we propose TIDE, which augments the standard transfo...
| Authors | Ajay Jaiswal, Lauren Hannah, Han-Byul Kim et al. |
|---|---|
| Primary category | cs.CL |
| Published | 7 May 2026 |
| Last updated at source | 7 May 2026 |
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