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TAS-Balanced: topic-aware batches and margin-balanced retriever teaching

Contribution grade

Dense retrieval training · Human-designed research method or resource

Reference score105,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Clustered training queries once, sampled topically related batches and balanced positive/negative passage pairs by teacher-score margins, combining pairwise cross-encoder and in-batch ColBERT teacher signals.

Scientific scope

Clustered training queries once, sampled topically related batches and balanced positive/negative passage pairs by teacher-score margins, combining pairwise cross-encoder and in-batch ColBERT teacher signals. Teacher inference, reused teacher scores and one-time query clustering have costs even when omitted from the student loop. Single-GPU timing and retrieval latency use the stated hardware/index configuration. Balanced teacher margins do not certify relevance labels or eliminate false negatives.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Teacher inference, reused teacher scores and one-time query clustering have costs even when omitted from the student loop. Single-GPU timing and retrieval latency use the stated hardware/index configuration. Balanced teacher margins do not certify relevance labels or eliminate false negatives.

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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