AI RESEARCH
Attention Calibration for Position-Fair Dense Information Retrieval
arXiv CS.CL
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ArXi:2606.02737v1 Announce Type: cross Dense retrieval models exhibit positional bias: retrieval effectiveness degrades when relevant information appears later in a passage (Zeng, 2025). We ask whether this bias can be reduced at inference time, without re