Skip to content
English

Switch theme

arXiv 2609.31620 · cs.CV · 2026-09-25

FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders

Hongyang Du, Yunfei Xie, Junjie Ye, Jiawei Yang, Xiaoyan Cong, Haodong Zhang, Yongchao Huang, Haiyu Wu and 8 more

USC Physical Superintelligence (PSI) Lab

In latest · #85 Added on 2026-10-21

One-line takeaway

FuseReg learns regularised layer fusion to ease the reconstruction-generation trade-off in representation autoencoders.

FuseReg 用可训练的层融合加正则,缓解表征自编码器在重建和生成之间的取舍。

138HF upvotes
17GitHub stars
1Citations (Semantic Scholar)
61.4Buzz score

Read on arXiv PDF Hugging Face discussion Code Project page

About this data

Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.

The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.

Data updated: Latest AI papers(UTC+8)