Papers with KV-efficient methods
Value Residual Learning (2025.acl-long)
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| Challenge: | Existing decoder-only transformers fail to preserve initial token-level information in deeper layers. |
| Approach: | They propose a new architecture that incorporates value residual connections in addition to hidden state residuals. |
| Outcome: | The proposed architecture reduces KV cache size by nearly half with only a small performance penalty and can be integrated with other KV-efficient methods. |