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Aug 2026
SITA enables target-aware compression by organizing compressed interests into semantic structures through semantic identifiers learned via parallel semantic quantization, conditioned on the semantic identifier of the target item, and adaptively aggregates the corresponding structured interests to construct the target-s...
Rui Zhou, Bo Chen, Qinglin Jia et al.
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Preprint
Aug 2026
Semantic Subword Tokenization (SST) is proposed, which represents historical items as variable-length semantic subwords while preserving fixed-length target decoding and introduces Behavior-induced Co-occurrence Augmentation to inject coarse-grained semantic prefix transition signals.
Xin-Rui Miao, Mingjia Yin, Jiaqing Zhang et al.
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2025
A novel method, namely AnDPro, is proposed, which introduces a projection-based scoring function to more accurately measure token importance and guide more accurate token selection in key-Value cache eviction.
Zijie Geng, Jie Wang, Ziqi Liu et al.
· Neural Information Processin... · 6 citations
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The exact selection time for an isolated cycle of NOTEARS and DAGMA is derived, and a truth-free separation statistic predicts selection time on 320 official NOTEARS/DAGMA trajectories.
Rui Wu, Zongyuan Chen, Hong Xie et al.
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The resulting lesson is task-specific: a first stage for generated controls should be judged by control fidelity, downstream relevance, and graph compatibility together.
Rui Wu, Zongyuan Chen, Hong Xie et al.
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