IC-061The induction circuit in Mamba-130m is structurally analogous to the transformer induction circuit, with an off-by-one motif in SSM state writing

Junxuan Wang, Xuyang Ge, Wentao Shu, Qiong Tang, Yunhua Zhou, Zhengfu He, Xipeng Qiu

SourceTowards Universality: Studying Mechanistic Similarity Across Language Model Architectures

Using path patching on Mamba-130m, the authors identify the induction circuit: SSM states at layer 17 are critical for induction (logit drop of -9.65 to -10.16 when patched), with layer 20 showing a weaker effect. The key information flows into the SSM input c at position b1+1 rather than b1, meaning the local convolution layer aggregates tokens a and b into the SSM state at the next token position. This 'off-by-one' motif is absent in transformers, where the previous-token head and induction head operate directly on the relevant token positions. The same off-by-one pattern is observed in the IOI task.

Evidence
interventional
Key metric
Layer 17 logit diff: -9.65 (dist 8), -8.09 (dist 16), -8.73 (dist 32), -10.16 (dist 64), -8.44 (dist 128); Layer 20 logit diff: -2.02 to -0.66; c(17) at b1+1 logit diff: -9.69 to -16.84; x(17) at b1 logit diff: -9.11 to -15.17
Caveat
Circuit analysis is qualitative; the authors note they have not yet quantitatively measured circuit similarity with automated tools. The off-by-one mechanism's purpose is unclear. Results are on 128 randomly generated induction data points.
Model
Mamba Mamba-130m
Methods
Path Patching [primary]
Related work
In-context Learning and Induction Heads [context], Interpretability in the Wild: A Circuit for Indirect Object Identification in GPT-2 Small [builds-on]
Related findings
IC-060
Extraction
automatic-extraction