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train-test-mismatch

topic1 events
papersTODAY 04:00 UTC

Paper proposes content-based addressing to replace positional rotation in long-context attention

A new arXiv preprint argues that rotary position embeddings (RoPE) degrade as context windows grow, because the integer positions seen during inference differ from those used in training. The authors suggest determining attention rotation from content-based addressing rather than from a token's fixed index, aiming to remove this train-test mismatch. The work is a methodological proposal and cross-listing revision, not a released model or product.

long-context/position-embeddings/arxiv/attention