Overview

Hyper-connections generalize a standard residual skip by maintaining several parallel residual streams and learning how layers read from and mix them, adding a route to capacity beyond width or depth. Common designs include token-dependent, manifold-constrained mixers—often doubly stochastic—as well as orthogonal or spectrally constrained transforms, sparse updates, and tensorized low-rank parameterizations. They are studied in language-model pretraining and finetuning, as well as vision, diffusion, and speech tasks; researchers also use stream ablations and probes to understand how the connections affect model behavior. The central tension is that richer routing can improve performance and parameter efficiency, yet streams may collapse or remain near identity, while constraints that stabilize gradients can limit expressivity or add computational cost.

Latest papers

CardsList

18 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

  1. The Birkhoff Geometry of Manifold-Constrained Hyper-Connections: Two Channels, Vertex Viscosity, and Sinkhorn as a Retraction

    Oct 5, 2026Xiaoyu Li, Zhizhou Sha, Chiwun YangHyper-ConnectionsConstrained Optimization

  2. Residual-Stream Burden Shapes Representation Learning in Diffusion Transformers

    Sep 27, 2026Tongtong Liang, Siqi Kou, Ziqiao Xi +6Diffusion TransformerResidual Learning

  3. How Does mHC Use Its Residual Streams? Selective Routing and Near-Identity Mixing

    Sep 4, 2026Pengxiang Zhao, Xing Li, Xianzhi Yu +2Hyper-ConnectionsResidual Learning

  4. oHC: Orthogonal Hyper-Connections on SO(4) via Quaternions

    Sep 2, 2026Haoqiang Guo, Xuyi Chen, Bo Ke +5Hyper-ConnectionsTransformer

  5. TEMPER: Tensorized Efficient Manifold-constrained Parameterization for Expressive Residual Routing

    Aug 8, 2026Yuxuan Gu, Wuyang Zhou, Huijun Xing +1Residual LearningHyper-Connections

  6. Beyond Residual Connections: Manifold-Constrained Hyper-Connections for Robust Speaker Representation Learning

    Aug 6, 2026Zezhong Jin, Xiaoyu Wang, Zhe Li +4Audio Representation LearningResidual Learning

  7. Manifold-Constrained Hyper-Connections for Parameter-Efficient Finetuning

    Jul 20, 2026Valentijn Oldenburg, Floris de Kam, Bente Zuijdam +5TransformerHyper-Connections

  8. xHC: Expanded Hyper-Connections

    Jul 16, 2026Xiangdong Zhang, Xiaohan Qin, Sunan Zou +10Language Model PretrainingTransformer

  9. Analyzing Stream Collapse in Hyper-Connections: From Diagnosis to Mitigation

    Jun 2, 2026Ekaterina Alimaskina, Gleb Molodtsov, Aleksandr BeznosikovTransformerHyper-Connections

  10. Accelerating Birkhoff Projection for Manifold-Constrained Hyper-Connections

    May 26, 2026Chenrui Wang, Yixuan QiuHyper-Connections

  11. Hyperloop Transformers

    Apr 23, 2026Abbas Zeitoun, Lucas Torroba-Hennigen, Yoon KimLLM CompressionHyper-Connections

  12. Spectral-Sphere-Constrained Hyper-Connections

    Mar 21, 2026Zhaoyi Liu, Haichuan Zhang, Ang LiHyper-ConnectionsResidual Learning

  13. Ablate and Rescue: A Causal Analysis of Residual Stream Hyper-Connections

    Mar 16, 2026William Peng, Josheev Rai, Kevin Tseng +2TransformerHyper-Connections

  14. JPmHC Dynamical Isometry via Orthogonal Hyper-Connections

    Feb 20, 2026Biswa Sengupta, Jinhua Wang, Leo BrunswicHyper-ConnectionsResidual Learning