26 citations · 26 across the 2 of their papers we have counts for
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cs.AI2026
From Atoms to Trees: Building a Structured Feature Forest with Hierarchical Sparse Autoencoders
Yifan Luo, Yang Zhan, Jiedong Jiang +4
Sparse autoencoders (SAEs) have proven effective for extracting monosemantic features from large language models (LLMs), yet these features are typically identified in isolation. H…
cs.AI2020★ 26 cited
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
Cunchao Zhu, Muhao Chen, Changjun Fan +2
Large knowledge graphs often grow to store temporal facts that model the dynamic relations or interactions of entities along the timeline. Since such temporal knowledge graphs ofte…