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CORE: Improving Compositional Reasoning in MLLM Embedding via Reranker Distillation research paper by Alibaba (Qwen), 2026

Alibaba (Qwen) · Sep 3, 2026 · Reasoning · 0 citations · 26 upvotes · unverified

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What it shows

CORE distills compositional ranking judgments from a cross-attentive reranker into an embedding model via synthesized multi-level candidates and a Rank-KL objective, improving compositional retrieval without degrading standard performance.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Tingyu Song, Mingxin Li, Yanzhao Zhang and 5 more
arXiv
2609.04083 · PDF
Citations
0, 0 influential · Semantic Scholar
Upvotes
26 · Hugging Face
Lab
Alibaba (Qwen) · on Companies · on Quarterly

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 0Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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