יום שלישי, 15 בספטמבר 2026 LIVE
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כתבה arXiv cs.AI ·

תיקון שקיפות תשומת הלב לדחיסה צפה

Attention Calibration for Position-Fair Dense Retrieval
אורחות חדשות להתמודדות עם סקיפות עמדה בדחיסה צפה. פיתוח של DeepSeek.
תקציר מקורי באנגליתarXiv:2606.02737v2 Announce Type: replace-cross Abstract: Dense retrieval compresses a passage into a single vector, but this compression is positionally skewed: early content dominates the embedding, and retrieval degrades when the relevant span appears later. Prior work proposed an inference-time method that counteracts this skew by equalizing the pooling token's attention across passage segments. However, (i) it redistributes attention at a fixed strength, (ii) it forces the pooling token's attention to itself to a fixed basket-level mass despite substantial variation across layers and architectures, and (iii) its effect on retrieval has not been evaluated. We introduce a strength coefficient that interpolates between uncalibrated and fully equalized attention, together with an efficien
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