Author

Zhijie Nie

Beihang University

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Preprint Aug 2026

UEmbed: Unified Sparse and Dense Multimodal Embeddings

UEmbed (Unified Embedding), a decoder-only multimodal embedding model that produces both sparse lexical and dense representations in one causal forward pass, offers a new paradigm: it unifies dense and sparse embeddings in one model, while further extending sparse retrieval to unify text and multimodal inputs.

Tingyu Song, Mingxin Li, Yanzhao Zhang et al. · 2 citations

Preprint Aug 2026

DEPT: Document Embedding Preservation Tuning for Unified Query Expansion and Retrieval

Document Embedding Preservation Tuning (DEPT) is introduced, which keeps tuned document embeddings close to cached initial embeddings while allowing retrieval gradients to pass through straight-through decoding into the generator.

Jingyuan Wang, Richong Zhang, Zhijie Nie et al. · 0 citations

Book Open access Jul 2026

Constructing Hard-Positive Query–Document Pairs for Dense Retrieval via Phrase Representativeness

This work defines model-specific Token and Phrase Representativeness Scores (TRS/PRS) to discover tokens and key phrases that appear in a document but are poorly expressed by its embedding, which improve retrieval on a constructed hard-positive benchmark and can also improve standard in-domain retrieval benchmarks.

Zhanyu Wu, Richong Zhang, Zhijie Nie · Annual International ACM SIG... · 0 citations