研究MLP的跳跃连接能否被吸收进无残差结构,发现多数情况下不可能。
Can an MLP Absorb Its Own Skip Connection?
- 通过度分析和线性化论证,证明多数激活函数下跳跃连接无法吸收
- ReLU/GELU在特定权重条件下可吸收,但该条件非通用(概率为0)
- 结果揭示残差与无残差模型函数类本质不同,适合深度学习理论研究者
我们研究单隐藏层MLP中跳跃连接能否被吸收进同宽度的无残差MLP。对于可逆线性跳跃分支(如Hyper-Connections及其流形约束变体),问题退化为恒等跳跃情形。对于次数k≠1的齐次激活函数(如ReLU²和ReGLU),由度数论证可知吸收必然不可能。对于门控激活函数(如SwiGLU、GeGLU),若门控函数在原点可微且g(0)=0,线性化论证也得出相同结论。这些不可能性结果可推广至任意深度:使用此类激活函数的L个残差块组合,无法由同宽度的L个无残差块组合复制。对于无门控的ReLU和GELU,情况更复杂:在单块层面,吸收成立当且仅当存在大小至少为d的索引集S,使得W_down[:,S]W_up[S,:] = -I_d。该条件非泛性(在连续权重分布下几乎必然不成立),因此跳连与无残差MLP代表泛性上不相交的函数类。深层组合中是否仍保持不相交尚待证明。
原文摘要 · Abstract (English)
We study when a skip connection around a single-hidden-layer MLP can be absorbed into a residual-free MLP of the same width. We first show that for any architecture whose skip branch is an invertible linear map (including Hyper-Connections and their manifold-constrained variants), the problem reduces to the identity skip case. For homogeneous activations of degree $k \neq 1$, such as ReLU$^2$ and ReGLU, absorption is unconditionally impossible by a degree argument. For gated activations whose gate is differentiable at the origin with $g(0) = 0$, including SwiGLU and GeGLU, a linearization argument gives the same conclusion. These impossibility results extend to arbitrary depth: a composition of $L$ residual blocks using such activations cannot be replicated by any composition of $L$ residual-free blocks of the same width. For ungated ReLU and GELU, the situation is richer. For generic weight matrices, absorption holds at the single-block level if and only if there exists an index set $S$ of size at least $d$ such that $W_{\mathrm{down}}[:,S]\,W_{\mathrm{up}}[S,:] = -I_d$. This condition is non-generic (it fails with probability one under continuous weight distributions), so skip-connected and residual-free MLPs of the same width represent generically disjoint function classes. Whether this disjointness persists for deep compositions of ReLU or GELU blocks remains open.
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