Paper Detail

Selective State-Space Adaptation and Retrieval for Language Model Reasoning

Atahan Dokme, Larry Heck

arxiv Score 14.8

Published 2026-07-21 · First seen 2026-07-22

General AI

Abstract

Low-rank adaptation introduces a static learned update applied identically to every input. The update provides task-level adaptation but does not explicitly represent token-level or instance-level state variation. A family of adapters is proposed that introduces selective state-space recurrence at two complementary granularities. At the token level, \textbf{MaLoRA} (Mamba-modulated low-rank adaptation) makes the adapter's scaling factor a dynamic input-dependent function with recurrent state across tokens, in contrast to the stateless modulators of prior work. At the context level, \textbf{MaRA} (Mamba Retrieval Adapter) tracks cross-segment state and selects the segments most relevant to the query, before the modulated language model generates its answer. Across three frozen backbones (Qwen-2.5-7B, Llama-3.1-8B, Gemma-2-9B) and two reasoning benchmarks (MuSiQue, 2WikiMultihopQA), the family improves reasoning accuracy on every cell of the $3{\times}2$ grid, by $+6.8$ F1 ($+10.5\%$ relative) on average and up to $+9.3$ F1 ($+18.2\%$ relative) on the hardest cell over the LoRA baseline, and the token-level gains carry to RULER QA-2 under length stress.

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BibTeX

@article{dokme2026selective,
  title = {Selective State-Space Adaptation and Retrieval for Language Model Reasoning},
  author = {Atahan Dokme and Larry Heck},
  year = {2026},
  abstract = {Low-rank adaptation introduces a static learned update applied identically to every input. The update provides task-level adaptation but does not explicitly represent token-level or instance-level state variation. A family of adapters is proposed that introduces selective state-space recurrence at two complementary granularities. At the token level, \textbackslash{}textbf\{MaLoRA\} (Mamba-modulated low-rank adaptation) makes the adapter's scaling factor a dynamic input-dependent function with recurrent state acr},
  url = {https://arxiv.org/abs/2607.19326},
  keywords = {cs.CL},
  eprint = {2607.19326},
  archiveprefix = {arXiv},
}

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