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ANCE: asynchronously refreshed corpus negatives for dense retrieval

Contribution grade

Dense retrieval training · Human-designed research method or resource

Reference score130,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Mined hard negatives from an approximate nearest-neighbor index of the corpus while a parallel inferencer periodically re-encoded documents and refreshed the index from newer training checkpoints.

Scientific scope

Mined hard negatives from an approximate nearest-neighbor index of the corpus while a parallel inferencer periodically re-encoded documents and refreshed the index from newer training checkpoints. Asynchronous refresh permits stale negatives and incurs re-encoding/index costs; it does not exactly eliminate every train-test distribution gap. Uses inherited encoders, nearest-neighbor search and contrastive losses. Source speedups depend on baselines and workload, not unconditional100x acceleration.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Asynchronous refresh permits stale negatives and incurs re-encoding/index costs; it does not exactly eliminate every train-test distribution gap. Uses inherited encoders, nearest-neighbor search and contrastive losses. Source speedups depend on baselines and workload, not unconditional100x acceleration.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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