Controlled experiments on frozen embeddings show per-sentence difficulty adaptation fails to help while pair-level gating by a held-out signal gives modest gains on larger tasks.
Distilling dense representations for ranking using tightly-coupled teachers.arXiv preprint arXiv:2010.11386, 2020
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A hybrid supervision method for bi-encoder retrievers combines graded relevance from teacher models, production retrieval priors, and selective engagement to improve relevance and NDCG over Walmart's current sponsored search system.
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When Does Complexity Conditioning Help a Frozen Sentence Embedding? A Controlled Study of Per-Sentence and Pair-Level Difficulty Adaptation
Controlled experiments on frozen embeddings show per-sentence difficulty adaptation fails to help while pair-level gating by a held-out signal gives modest gains on larger tasks.
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Unified Supervision for Walmart's Sponsored Search Retrieval via Joint Semantic Relevance and Behavioral Engagement Modeling
A hybrid supervision method for bi-encoder retrievers combines graded relevance from teacher models, production retrieval priors, and selective engagement to improve relevance and NDCG over Walmart's current sponsored search system.